Sample records for 3-d ultrasonic imaging

Due to the properties of convenience and non-invasion, ultrasound has become an essential tool for diagnosis of fetal abnormality during women pregnancy in obstetrics. However, the 'noisy and blurry' nature of ultrasound data makes the rendering of the data a challenge in comparison with MRI and CT images. In spite of the speckle noise, the unwanted objects usually occlude the target to be observed. In this paper, we proposed a new system that can effectively depress the speckle noise, extract the target object, and clearly render the 3D fetal image in almost real-time from 3D ultrasound image data. The system is based on a deformable model that detects contours of the object according to the local image feature of ultrasound. Besides, in order to accelerate rendering speed, a thin shell is defined to separate the observed organ from unrelated structures depending on those detected contours. In this way, we can support quick 3D display of ultrasound, and the efficient visualization of 3D fetal ultrasound thus becomes possible.

The objective of this research is to develop a new robust fingerprint identification technology based upon forming surface-subsurface (under skin) ultrasonic3Dimages of the finger pads. The presented work aims to create specialized ultrasonic scanning methods for biometric purposes. Preliminary research has demonstrated the applicability of acoustic microscopy for fingerprint reading. The additional information from internal skin layers and dermis structures contained in the scan can essentially improve confidence in the identification. Advantages of this system include high resolution and quick scanning time. Operating in pulse-echo mode provides spatial resolution up to 0.05 mm. Technology advantages of the proposed technology are the following: • Full-range scanning of the fingerprint area "nail to nail" (2.5 x 2.5 cm) can be done in less than 5 sec with a resolution of up to 1000 dpi. • Collection of information about the in-depth structure of the fingerprint realized by the set of spherically focused 50 MHz acoustic lens provide the resolution ~ 0.05 mm or better • In addition to fingerprints, this technology can identify sweat porous at the surface and under the skin • No sensitivity to the contamination of the finger's surface • Detection of blood velocity using Doppler effect can be implemented to distinguish living specimens • Utilization as polygraph device • Simple connectivity to fingerprint databases obtained with other techniques • The digitally interpolated images can then be enhanced allowing for greater resolution • Method can be applied to fingernails and underlying tissues, providing more information • A laboratory prototype of the biometrics system based on these described principles was designed, built and tested. It is the first step toward a practical implementation of this technique.

In order to meet the requirements of rising flexibility and an automated material inspection in a small batch production environment, an automatically changeable ultrasound sensor tool for milling machines has been developed. This system enables an automated ultrasonic inspection of varying parts to be carried out directly on a machining center and visualizes hidden geometries and material imperfections three-dimensionally. The sensor tool is based on commercialized ultrasonic squirter-probes, which are able to use the cooling lubricant for sound coupling. During the measurement recordings, the milling machine's axes move the sensor numerical-controlled across the workpiece. By this means, automated material inspection tasks can be performed very cost-effectively without setting up separate testing facilities. 4- or 5-axes kinematics capacitates the system to check even very complex-shaped parts.

Conventional three dimensional (3D) ghost imaging measures range of target based on pulse fight time measurement method. Due to the limit of data acquisition system sampling rate, range resolution of the conventional 3D ghost imaging is usually low. In order to take off the effect of sampling rate to range resolution of 3D ghost imaging, a heterodyne 3D ghost imaging (HGI) system is presented in this study. The source of HGI is a continuous wave laser instead of pulse laser. Temporal correlation and spatial correlation of light are both utilized to obtain the range image of target. Through theory analysis and numerical simulations, it is demonstrated that HGI can obtain high range resolution image with low sampling rate.

An ultrasonic nondestructive methodology is proposed for the assessment of low velocity impact damage in a 3D woven composite material. The output data is intended for material scientists and numerical scientists to validate the damage tolerance performance of the manufactured materials and the reliability of damage modeling predictions. A depth-dependent threshold based on the reflectivity of flat bottom holes is applied to the ultrasonic data to remove the structural noise and isolate echoes of interest. The methodology was applied to a 3 mm thick 3D woven composite plate impacted with different energies. An artificial 3D representation of the detected echoes is proposed to enhance the spatial perception of the generated damage by the end user. The paper finally highlights some statistics made on the detected echoes to quantitatively assess the impact damage resistance of the tested specimens.

This paper shows the first application of in situ manipulation of discontinuous fibrous structure mid-print, within a 3D printed polymeric composite architecture. Currently, rapid prototyping methods (fused filament fabrication, stereolithography) are gaining increasing popularity within the engineering commnity to build structural components. Unfortunately, the full potential of these components is limited by the mechanical properties of the materials used. The aim of this study is to create and demonstrate a novel method to instantaneously orient micro-scale glass fibres within a selectively cured photocurable resin system, using ultrasonic forces to align the fibres in the desired 3D architecture. To achieve this we have mounted a switchable, focused laser module on the carriage of a three-axis 3D printing stage, above an in-house ultrasonic alignment rig containing a mixture of photocurable resin and discontinuous 14 μm diameter glass fibre reinforcement(50 μm length). In our study, a suitable print speed of 20 mm s-1 was used, which is comparable to conventional additive layer techniques. We show the ability to construct in-plane orthogonally aligned sections printed side by side, where the precise orientation of the configurations is controlled by switching the ultrasonic standing wave profile mid-print. This approach permits the realisation of complex fibrous architectures within a 3D printed landscape. The versatile nature of the ultrasonic manipulation technique also permits a wide range of particle types (diameters, aspect ratios and functions) and architectures (in-plane, and out-plane) to be patterned, leading to the creation of a new generation of fibrous reinforced composites for 3D printing.

Structural health monitoring (SHM) for the detection of damage in aerospace materials is an important area of research at NASA. Ultrasonic guided Lamb waves are a promising SHM damage detection technique since the waves can propagate long distances. For complicated flaw geometries experimental signals can be difficult to interpret. High performance computing can now handle full 3-dimensional (3D) simulations of elastic wave propagation in materials. We have developed and implemented parallel 3D elastodynamic finite integration technique (3D EFIT) code to investigate ultrasound scattering from flaws in materials. EFIT results have been compared to experimental data and the simulations provide unique insight into details of the wave behavior. This type of insight is useful for developing optimized experimental SHM techniques. 3D EFIT can also be expanded to model wave propagation and scattering in anisotropic composite materials.

To assist with the design and validation of testing procedures for NDT, add-on modules have been developed for AutoCAD® 2000. One of the modules computes and displays ultrasonic3D ray tracing. Another determines paths between two points, for instance a probe and a target or two probes. The third module displays phased array operational modes and calculates element delays for phased array operation. The modules can be applied to simple or complex solid model components.

Quantitative 3Dimaging is becoming an increasingly popular and powerful approach to investigate plant growth and development. With the increased use of 3Dimage analysis, standards to ensure the accuracy and reproducibility of these data are required. This commentary highlights how image acquisition and postprocessing can introduce artifacts into 3Dimage data and proposes steps to increase both the accuracy and reproducibility of these analyses. It is intended to aid researchers entering the field of 3Dimage processing of plant cells and tissues and to help general readers in understanding and evaluating such data. PMID:25804539

Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in 3D based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32 × 32 matrix-array probe. Its ability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3D Shear-Wave Imaging, 3D Ultrafast Doppler Imaging, and, finally, 3D Ultrafast combined Tissue and Flow Doppler Imaging. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3D Ultrafast Doppler was used to obtain 3D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, at thousands of volumes per second, the complex 3D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, as well as the 3D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3D Ultrafast Ultrasound Imaging for the 3D mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra—and inter-observer variability.

Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative real-time imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in three dimensions based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32×32 matrix-array probe. Its capability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3-D Shear-Wave Imaging, 3-D Ultrafast Doppler Imaging and finally 3D Ultrafast combined Tissue and Flow Doppler. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3-D Ultrafast Doppler was used to obtain 3-D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, for the first time, the complex 3-D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, and the 3-D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3-D Ultrafast Ultrasound Imaging for the 3-D real-time mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra- and inter-observer variability. PMID:25207828

Interactive computer-based simulation is gaining acceptance for craniofacial surgical planning. Subjective visualization without objective measurement capability, however, severely limits the value of simulation since spatial accuracy must be maintained. This study investigated the error sources involved in one method of surgical simulation evaluation. Linear and angular measurement errors were found to be within +/- 1 mm and 1 degree. Surface match of scanned objects was slightly less accurate, with errors up to 3 voxels and 4 degrees, and Boolean subtraction methods were 93 to 99% accurate. Once validated, these testing methods were applied to objectively compare craniofacial surgical simulations to post-operative outcomes, and verified that the form of simulation used in this study yields accurate depictions of surgical outcome. However, to fully evaluate surgical simulation, future work is still required to test the new methods in sufficient numbers of patients to achieve statistically significant results. Once completely validated, simulation cannot only be used in pre-operative surgical planning, but also as a post-operative descriptor of surgical and traumatic physical changes. Validated image comparison methods can also show discrepancy of surgical outcome to surgical plan, thus allowing evaluation of surgical technique. PMID:11098409

Since many years, integral imaging has been discussed as a technique to overcome the limitations of standard still photography imaging systems where a three-dimensional scene is irrevocably projected onto two dimensions. With the success of 3D stereoscopic movies, a huge interest in capturing three-dimensional motion picture scenes has been generated. In this paper, we present a test bench integral imaging camera system aiming to tailor the methods of light field imaging towards capturing integral 3D motion picture content. We estimate the hardware requirements needed to generate high quality 3D holoscopic images and show a prototype camera setup that allows us to study these requirements using existing technology. The necessary steps that are involved in the calibration of the system as well as the technique of generating human readable holoscopic images from the recorded data are discussed.

3D surface imaging refers to methods that generate a 3D surface representation of objects of a scene under viewing. Laser-based 3D surface imaging systems are commonly used in manufacturing, robotics and biomedical research. Although laser-based systems provide satisfactory solutions for most applications, there are situations where non laser-based approaches are preferred. The issues that make alternative methods sometimes more attractive are: (1) real-time data capturing, (2) eye-safety, (3) portability, and (4) work distance. The focus of this presentation is on generating a 3D surface from multiple 2D projected images using CCD cameras, without a laser light source. Two methods are presented: stereo vision and depth-from-focus. Their applications are described.

We designed and assembled a portable 3-D miniature microscopic image system with the size of 35x35x105 mm3 . By integrating a microlens array (MLA) into the optical train of a handheld microscope, the biological specimen's image will be captured for ease of use in a single shot. With the light field raw data and program, the focal plane can be changed digitally and the 3-Dimage can be reconstructed after the image was taken. To localize an object in a 3-D volume, an automated data analysis algorithm to precisely distinguish profundity position is needed. The ability to create focal stacks from a single image allows moving or specimens to be recorded. Applying light field microscope algorithm to these focal stacks, a set of cross sections will be produced, which can be visualized using 3-D rendering. Furthermore, we have developed a series of design rules in order to enhance the pixel using efficiency and reduce the crosstalk between each microlens for obtain good image quality. In this paper, we demonstrate a handheld light field microscope (HLFM) to distinguish two different color fluorescence particles separated by a cover glass in a 600um range, show its focal stacks, and 3-D position.

An imaging system is described which can be used to either passively search for sources of ultrasonics or as an active phase imaging system. which can image fires. gas leaks, or air temperature gradients. This system uses an array of ultrasonic receivers coupled to an ultrasound collector or lens to provide an electronic image of the ultrasound intensity in a selected angular region of space. A system is described which includes a video camera to provide a visual reference to a region being examined for ultrasonic signals.

In this paper, we propose a method by means of light field imaging under structured illumination to deal with high dynamic range 3Dimaging. Fringe patterns are projected onto a scene and modulated by the scene depth then a structured light field is detected using light field recording devices. The structured light field contains information about ray direction and phase-encoded depth, via which the scene depth can be estimated from different directions. The multidirectional depth estimation can achieve high dynamic 3Dimaging effectively. We analyzed and derived the phase-depth mapping in the structured light field and then proposed a flexible ray-based calibration approach to determine the independent mapping coefficients for each ray. Experimental results demonstrated the validity of the proposed method to perform high-quality 3Dimaging for highly and lowly reflective surfaces. PMID:27607639

Most applications of thoracic EIT use a single plane of electrodes on the chest from which a transverse image 'slice' is calculated. However, interpretation of EIT images is made difficult by the large region above and below the electrode plane to which EIT is sensitive. Volumetric EIT images using two (or more) electrode planes should help compensate, but are little used currently. The Graz consensus reconstruction algorithm for EIT (GREIT) has become popular in lung EIT. One shortcoming of the original formulation of GREIT is its restriction to reconstruction onto a 2D planar image. We present an extension of the GREIT algorithm to 3D and develop open-source tools to evaluate its performance as a function of the choice of stimulation and measurement pattern. Results show 3D GREIT using two electrode layers has significantly more uniform sensitivity profiles through the chest region. Overall, the advantages of 3D EIT are compelling. PMID:27203184

Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received

The moiré fringes method and their analysis up to medical and entertainment applications are discussed in this paper. We describe the procedure of capturing 3Dimages with an Inspeck Camera that is a real-time 3D shape acquisition system based on structured light techniques. The method is a high-resolution one. After processing the images, using computer, we can use the data for creating laser fashionable objects by engraving them with a Q-switched Nd:YAG. In medical field we mention the plastic surgery and the replacement of X-Ray especially in pediatric use.

In this paper, we propose a robust camera tracking method that uses disparity images computed from known parameters of 3D camera and multiple epipolar constraints. We assume that baselines between lenses in 3D camera and intrinsic parameters are known. The proposed method reduces camera motion uncertainty encountered during camera tracking. Specifically, we first obtain corresponding feature points between initial lenses using normalized correlation method. In conjunction with matching features, we get disparity images. When the camera moves, the corresponding feature points, obtained from each lens of 3D camera, are robustly tracked via Kanade-Lukas-Tomasi (KLT) tracking algorithm. Secondly, relative pose parameters of each lens are calculated via Essential matrices. Essential matrices are computed from Fundamental matrix calculated using normalized 8-point algorithm with RANSAC scheme. Then, we determine scale factor of translation matrix by d-motion. This is required because the camera motion obtained from Essential matrix is up to scale. Finally, we optimize camera motion using multiple epipolar constraints between lenses and d-motion constraints computed from disparity images. The proposed method can be widely adopted in Augmented Reality (AR) applications, 3D reconstruction using 3D camera, and fine surveillance systems which not only need depth information, but also camera motion parameters in real-time.

We have demonstrated high definition and improved resolution using a novel scanning system integrated with a commercial ultrasound machine. The result is a volumetric 3D ultrasound data set that can be visualized using standard techniques. Unlike other 3D ultrasound images, image quality is improved from standard 2D data. Image definition and bandwidth is improved using patent pending techniques. The system can be used to image patients or wounded soldiers for general imaging of anatomy such as abdominal organs, extremities, and the neck. Although the risks associated with x-ray carcinogenesis are relatively low at diagnostic dose levels, concerns remain for individuals in high risk categories. In addition, cost and portability of CT and MRI machines can be prohibitive. In comparison, ultrasound can provide portable, low-cost, non-ionizing imaging. Previous clinical trials comparing ultrasound to CT were used to demonstrate qualitative and quantitative improvements of ultrasound using the Sandia technologies. Transverse leg images demonstrated much higher clarity and lower noise than is seen in traditional ultrasound images. An x-ray CT scan was provided of the same cross-section for comparison. The results of our most recent trials demonstrate the advantages of 3D ultrasound and motion compensation compared with 2D ultrasound. Metal objects can also be observed within the anatomy. PMID:10168958

A system for dynamic mapping of broadband ultrasound fields has been designed, with high frame rate photoacoustic imaging in mind. A Fabry-Pérot interferometric ultrasound sensor was interrogated using a coherent light single-pixel camera. Scrambled Hadamard measurement patterns were used to sample the acoustic field at the sensor, and either a fast Hadamard transform or a compressed sensing reconstruction algorithm were used to recover the acoustic pressure data. Frame rates of 80 Hz were achieved for 32x32 images even though no specialist hardware was used for the on-the-fly reconstructions. The ability of the system to obtain photocacoustic images with data compressions as low as 10% was also demonstrated.

ViSUAl-D (VIsual Sar Using ALl Dimensions), a 2004 DARPA/IXO seedling effort, is developing a capability for reliable high confidence ID from standoff ranges. Recent conflicts have demonstrated that the warfighter would greatly benefit from the ability to ID targets beyond visual and electro-optical ranges[1]. Forming optical-quality SAR images while exploiting full polarization, wide angles, and large bandwidth would be key evidence such a capability is achievable. Using data generated by the Xpatch EM scattering code, ViSUAl-D investigates all degrees of freedom available to the radar designer, including 6 GHz bandwidth, full polarization and angle sampling over 2π steradians (upper hemisphere), in order to produce a "literal" image or representation of the target. This effort includes the generation of a "Gold Standard" image that can be produced at X-band utilizing all available target data. This "Gold Standard" image of the backhoe will serve as a test bed for future more relevant military targets and their image development. The seedling team produced a public release data which was released at the 2004 SPIE conference, as well as a 3D "Gold Standard" backhoe image using a 3Dimage formation algorithm. This paper describes the full backhoe data set, the image formation algorithm, the visualization process and the resulting image.

Manufacturers often express the performance of a 3Dimaging device in various non-uniform ways for the lack of internationally recognized standard requirements for metrological parameters able to identify the capability of capturing a real scene. For this reason several national and international organizations in the last ten years have been developing protocols for verifying such performance. Ranging from VDI/VDE 2634, published by the Association of German Engineers and oriented to the world of mechanical 3D measurements (triangulation-based devices), to the ASTM technical committee E57, working also on laser systems based on direct range detection (TOF, Phase Shift, FM-CW, flash LADAR), this paper shows the state of the art about the characterization of active range devices, with special emphasis on measurement uncertainty, accuracy and resolution. Most of these protocols are based on special objects whose shape and size are certified with a known level of accuracy. By capturing the 3D shape of such objects with a range device, a comparison between the measured points and the theoretical shape they should represent is possible. The actual deviations can be directly analyzed or some derived parameters can be obtained (e.g. angles between planes, distances between barycenters of spheres rigidly connected, frequency domain parameters, etc.). This paper shows theoretical aspects and experimental results of some novel characterization methods applied to different categories of active 3Dimaging devices based on both principles of triangulation and direct range detection.

A system has been developed to produce live 3D volume renderings from an MR scanner. Whereas real-time 2D MR imaging has been demonstrated by several groups, 3D volumes are currently rendered off-line to gain greater understanding of anatomical structures. For example, surgical planning is sometimes performed by viewing 2D images or 3D renderings from previously acquired image data. A disadvantage of this approach is misregistration which could occur if the anatomy changes due to normal muscle contractions or surgical manipulation. The ability to produce volume renderings in real-time and present them in the magnet room could eliminate this problem, and enable or benefit other types of interventional procedures. The system uses the data stream generated by a fast 2D multi- slice pulse sequence to update a volume rendering immediately after a new slice is available. We demonstrate some basic types of user interaction with the rendering during imaging at a rate of up to 20 frames per second.

Canadian women have a one in nine chance of developing breast cancer during their lifetime. Mammography is the most common imaging technology used for breast cancer detection in its earliest stages through screening programs. Clusters of microcalcifications are primary indicators of breast cancer; the shape, size and number may be used to determine whether they are malignant or benign. However, overlapping images of calcifications on a mammogram hinder the classification of the shape and size of each calcification and a misdiagnosis may occur resulting in either an unnecessary biopsy being performed or a necessary biopsy not being performed. The introduction of 3Dimaging techniques such as standard photogrammetry may increase the confidence of the radiologist when making his/her diagnosis. In this paper, traditional analytical photogrammetric techniques for the 3D mathematical reconstruction of microcalcifications are presented. The techniques are applied to a specially designed and constructed x-ray transparent Plexiglas phantom (control object). The phantom was embedded with 1.0 mm x-ray opaque lead pellets configured to represent overlapping microcalcifications. Control points on the phantom were determined by standard survey methods and hand measurements. X-ray films were obtained using a LORAD M-III mammography machine. The photogrammetric techniques of relative and absolute orientation were applied to the 2D mammographic films to analytically generate a 3D depth map with an overall accuracy of 0.6 mm. A Bundle Adjustment and the Direct Linear Transform were used to confirm the results. PMID:15649085

Biometrics is an important field which studies different possible ways of personal identification. Among a number of existing biometric techniques fingerprint recognition stands alone - because very large database of fingerprints has already been acquired. Also, fingerprints are an important evidence that can be collected at a crime scene. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. Ultrasonic method of fingerprint imaging was originally introduced over a decade as the mapping of the reflection coefficient at the interface between the finger and a covering plate and has shown very good reliability and free from imperfections of previous two methods. This work introduces a newer development of the ultrasonic fingerprint imaging, focusing on the imaging of the internal structures of fingerprints (including sweat pores) with raw acoustic resolution of about 500 dpi (0.05 mm) using a scanning acoustic microscope to obtain images and acoustic data in the form of 3D data array. C-scans from different depths inside the fingerprint area of fingers of several volunteers were obtained and showed good contrast of ridges-and-valleys patterns and practically exact correspondence to the standard ink-and-paper prints of the same areas. Important feature reveled on the acoustic images was the clear appearance of the sweat pores, which could provide additional means of identification.

This paper proposes a new high capacity Steganographic scheme using 3D geometric models. The novel algorithm re-triangulates a part of a triangle mesh and embeds the secret information into newly added position of triangle meshes. Up to nine bits of secret data can be embedded into vertices of a triangle without causing any changes in the visual quality and the geometric properties of the cover image. Experimental results show that the proposed algorithm is secure, with high capacity and low distortion rate. Our algorithm also resists against uniform affine transformations such as cropping, rotation and scaling. Also, the performance of the method is compared with other existing 3D Steganography algorithms. [Figure not available: see fulltext.

The objective of this study was to visualize, in a novel way, the morphological characteristics of bovine teats to gain a better understanding of the detailed teat morphology. We applied silicone casting and 3D digital imaging in order to obtain a more detailed image of the teat structures than that seen in previous studies. Teat samples from 65 dairy cows over 12 months of age were obtained from cows slaughtered at an abattoir. The teats were classified according to the teat condition scoring used in Finland and the lengths of the teat canals were measured. Silicone molds were made from the external teat surface surrounding the teat orifice and from the internal surface of the teat consisting of the papillary duct, Fürstenberg's rosette, and distal part of the teat cistern. The external and internal surface molds of 35 cows were scanned with a 3D laser scanner. The molds and the digital 3D models were used to evaluate internal and external teat surface morphology. A number of measurements were taken from the silicone molds. The 3D models reproduced the morphology of the teats accurately with high repeatability. Breed didn't correlate with the teat classification score. The rosette was found to have significant variation in its size and number of mucosal folds. The internal surface morphology of the rosette did not correlate with the external surface morphology of the teat implying that it is relatively independent of milking parameters that may impact the teat canal and the external surface of the teat. PMID:25382725

Extracting fault, unconformity, and horizon surfaces from a seismic image is useful for interpretation of geologic structures and stratigraphic features. Although interpretation of these surfaces has been automated to some extent by others, significant manual effort is still required for extracting each type of these geologic surfaces. I propose methods to automatically extract all the fault, unconformity, and horizon surfaces from a 3D seismic image. To a large degree, these methods just involve image processing or array processing which is achieved by efficiently solving partial differential equations. For fault interpretation, I propose a linked data structure, which is simpler than triangle or quad meshes, to represent a fault surface. In this simple data structure, each sample of a fault corresponds to exactly one image sample. Using this linked data structure, I extract complete and intersecting fault surfaces without holes from 3D seismic images. I use the same structure in subsequent processing to estimate fault slip vectors. I further propose two methods, using precomputed fault surfaces and slips, to undo faulting in seismic images by simultaneously moving fault blocks and faults themselves. For unconformity interpretation, I first propose a new method to compute a unconformity likelihood image that highlights both the termination areas and the corresponding parallel unconformities and correlative conformities. I then extract unconformity surfaces from the likelihood image and use these surfaces as constraints to more accurately estimate seismic normal vectors that are discontinuous near the unconformities. Finally, I use the estimated normal vectors and use the unconformities as constraints to compute a flattened image, in which seismic reflectors are all flat and vertical gaps correspond to the unconformities. Horizon extraction is straightforward after computing a map of image flattening; we can first extract horizontal slices in the flattened space

There has been a lack of an effective NDE technique to locate internal defects within wooden logs. The few available elastic wave propagation based techniques are limited to predicting E values. Other techniques such as X-rays have not been very successful in detecting internal defects in logs. If defects such as embedded metals could be identified before the sawing process, the saw mills could significantly increase their production by reducing the probability of damage to the saw blade and the associated downtime and the repair cost. Also, if the internal defects such as knots and decayed areas could be identified in logs, the sawing blade can be oriented to exclude the defective portion and optimize the volume of high valued lumber that can be obtained from the logs. In this research, GPR has been successfully used to locate internal defects (knots, decays and embedded metals) within the logs. This paper discusses GPR imaging and mapping of the internal defects using both 2D and 3D interpretation methodology. Metal pieces were inserted in a log and the reflection patterns from these metals were interpreted from the radargrams acquired using 900 MHz antenna. Also, GPR was able to accurately identify the location of knots and decays. Scans from several orientations of the log were collected to generate 3D cylindrical volume. The actual location of the defects showed good correlation with the interpreted defects in the 3D volume. The time/depth slices from 3D cylindrical volume data were useful in understanding the extent of defects inside the log.

Three-dimensional (3-D) median filtering is very useful to eliminate speckle noise from a medical imaging source, such as functional magnetic resonance imaging (fMRI) and ultrasonicimaging. 3-D median filtering is characterized by its higher computation complexity. N 3(N 3-1)/2 comparison operations would be required for 3-D median filtering with N×N×N window if the conventional bubble-sorting algorithm is adopted. In this paper, an efficient fast algorithm for 3-D median filtering was presented, which considerably reduced the computation complexity for extracting the median of a 3-D data array. Compared to the state-of-the-art, the proposed method could reduce the computation complexity of 3-D median filtering by 33%. It results in efficiently reducing the system delay of the 3-D median filter by software implementation, and the system cost and power consumption by hardware implementation.

The performance of ATR systems can potentially be improved by using three-dimensional (3-D) SAR images instead of the traditional two-dimensional SAR images or one-dimensional range profiles. 3-D SAR image formation of targets from radar backscattered data collected on wide angle, sparse apertures has been identified by AFRL as fundamental to building an object detection and recognition capability. A set of data has been released as a challenge problem. This paper describes a technique based on the concept of 3-D target grids aimed at the formation of 3-D SAR images of targets from sparse aperture data. The 3-D target grids capture the 3-D spatial and angular scattering properties of the target and serve as matched filters for SAR formation. The results of 3-D SAR formation using the backhoe public release data are presented.

In this paper, we present the system architecture of a 360 degree view 3Dimaging system. The system consists of multiple 3D sensors synchronized to take 3Dimages around the object. Each 3D camera employs a single high-resolution digital camera and a color-coded light projector. The cameras are synchronized to rapidly capture the 3D and color information of a static object or a live person. The color encoded structure lighting ensures the precise reconstruction of the depth of the object. A 3Dimaging system architecture is presented. The architecture employs the displacement of the camera and the projector to triangulate the depth information. The 3D camera system has achieved high depth resolution down to 0.1mm on a human head sized object and 360 degree imaging capability.

This paper introduces a semi-automatic method for buildings extraction through multiple-view aerial image analysis. The advantage of the used semi-automatic approach is that it allows processing of each building individually finding the parameters of buildings features extraction more precisely for each area. On the early stage the presented technique uses an extraction of line segments that is done only inside of areas specified manually. The rooftop hypothesis is used further to determine a subset of quadrangles, which could form building roofs from a set of extracted lines and corners obtained on the previous stage. After collecting of all potential roof shapes in all images overlaps, the epipolar geometry is applied to find matching between images. This allows to make an accurate selection of building roofs removing false-positive ones and to identify their global 3D coordinates given camera internal parameters and coordinates. The last step of the image matching is based on geometrical constraints in contrast to traditional correlation. The correlation is applied only in some highly restricted areas in order to find coordinates more precisely, in such a way significantly reducing processing time of the algorithm. The algorithm has been tested on a set of Milan's aerial images and shows highly accurate results.

In this paper, a novel approach to cardiac interventional navigation on 3D motion-compensated static roadmaps is presented. Current coronary interventions, e.g. percutaneous transluminal coronary angioplasties, are performed using 2D X-ray fluoroscopy. This comes along with well-known drawbacks like radiation exposure, use of contrast agent, and limited visualization, e.g. overlap and foreshortening, due to projection imaging. In the presented approach, the interventional device, i.e. the catheter, is tracked using an electromagnetic tracking system (MTS). Therefore, the catheters position is mapped into a static 3Dimage of the volume of interest (VOI) by means of an affine registration. In order to compensate for respiratory motion of the catheter with respect to the static image, a parameterized affine motion model is used which is driven by a respiratory sensor signal. This signal is derived from ultrasonic diaphragm tracking. The motion compensation for the heartbeat is done using ECG-gating. The methods are validated using a heart- and diaphragm-phantom. The mean displacement of the catheter due to the simulated organ motion decreases from approximately 9 mm to 1.3 mm. This result indicates that the proposed method is able to reconstruct the catheter position within the VOI accurately and that it can help to overcome drawbacks of current interventional procedures.

We are developing a flow cytometer that detects unique acoustic signature waves generated from single cells due to interactions between the cells and ultrasound waves. The generated acoustic waves depend on the size and biomechanical properties of the cells and are sufficient for identifying cells in the medium. A microfluidic system capable of focusing cells through a 10 x 10 μm ultrasound beam cross section was developed to facilitate acoustic measurements of single cells. The cells are streamlined in a hydro-dynamically 3D focused flow in a 300 x 300 μm channel made using PDMS. 3D focusing is realized by lateral sheath flows and an inlet needle (inner diameter 100 μm). The accuracy of the 3D flow focusing is measured using a dye and detecting its localization using confocal microscopy. Each flowing cell would be probed by an ultrasound pulse, which has a center frequency of 375 MHz and bandwidth of 250 MHz. The same probe would also be used for recording the scattered waves from the cells, which would be processed to distinguish the physical and biomechanical characteristics of the cells, eventually identifying them. This technique has potential applications in detecting circulating tumor cells, blood cells and blood-related diseases.

3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using an RF button electrode which is needle-like is being used to destroy tumor cells or stop bleeding currently. Now a 3D US guidance system has been developed to avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment. In this paper, we described two automated techniques, the 3D Hough Transform (3DHT) and the 3D Randomized Hough Transform (3DRHT), which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance. Based on the representation (Φ , θ , ρ , α ) of straight lines in 3D space, we used the 3DHT algorithm to segment needles successfully assumed that the approximate needle position and orientation are known in priori. The 3DRHT algorithm was developed to detect needles quickly without any information of the 3D US images. The needle segmentation techniques were evaluated using the 3D US images acquired by scanning water phantoms. The experiments demonstrated the feasibility of two 3D needle segmentation algorithms described in this paper.

In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.

It is the intention of this paper, to contribute to a sustainable future by providing objective object information based on 3D photography as well as promoting 3D photography not only for scientists, but also for amateurs. Due to the presentation of this article by CIPA Task Group 3 on "3D Photographs in Cultural Heritage", the presented samples are masterpieces of historic as well as of current 3D photography concentrating on cultural heritage. In addition to a report on exemplarily access to international archives of 3D photographs, samples for new 3D photographs taken with modern 3D cameras, as well as by means of a ground based high resolution XLITE staff camera and also 3D photographs taken from a captive balloon and the use of civil drone platforms are dealt with. To advise on optimum suited 3D methodology, as well as to catch new trends in 3D, an updated synoptic overview of the 3D visualization technology, even claiming completeness, has been carried out as a result of a systematic survey. In this respect, e.g., today's lasered crystals might be "early bird" products in 3D, which, due to lack in resolution, contrast and color, remember to the stage of the invention of photography.

Ames Laboratory scientist Song Zhang explains his real-time 3-Dimaging technology. The technique can be used to create high-resolution, real-time, precise, 3-Dimages for use in healthcare, security, and entertainment applications.

Real-time ultrasonic colour flow imaging, which was first demonstrated to be feasible only about a decade ago, has come into widespread clinical use. Ultrasound is scattered by ensembles of red blood cells. The ultrasonic frequency that gives the best signal-to-noise ratio for backscattering from blood depends on the required penetration. The frequency of ultrasound backscattered from flowing blood is shifted by the Doppler effect. The direction of flow can be determined by phase quadrature detection, and range selectivity can be provided by pulse-echo time-delay measurements. The Doppler frequency spectrum can be determined by Fourier analysis. Early two- and three-dimensional flow-imaging systems used slow manual scanning; velocity colour coding was introduced. Real-time colour flow imaging first became feasible when autocorrelation detection was used to extract the Doppler signal. Time-domain processing, which is a broad-band technique, was also soon shown to be practicable, for analysing both radio-frequency pulse-echo wavetrains and two-dimensional image speckle. Frequency- and time-domain processing both require effective cancellation of stationary echoes. The time-domain approach seems to have advantages in relation to both aliasing and the effects of attenuation in overlying tissues. Colour-coding schemes that can be interpreted without the need to refer to keys have been adopted, for both velocity and flow disturbance. Colour coding according to signal power has also been reintroduced. Three-dimensional display has been demonstrated. In interpreting colour flow images, it is important to understand the functions of critical system controls and the origins of artifacts. Various strategies can be adopted to increase the image frame rate. The problems of performance measurement and safety need to be kept under review. There are numerous opportunities for further development of ultrasonic colour flow imaging, including improvements in system design, methods of

Three-dimensionality is currently considered an important added value in imaging devices, and therefore the search for an optimum 3Dimaging and display technique is a hot topic that is attracting important research efforts. As main value, 3D monitors should provide the observers with different perspectives of a 3D scene by simply varying the head position. Three-dimensional imaging techniques have the potential to establish a future mass-market in the fields of entertainment and communications. Integral imaging (InI), which can capture true 3D color images, has been seen as the right technology to 3D viewing to audiences of more than one person. Due to the advanced degree of development, InI technology could be ready for commercialization in the coming years. This development is the result of a strong research effort performed along the past few years by many groups. Since Integral Imaging is still an emerging technology, the first aim of the "3DImaging and Display Laboratory" at the University of Valencia, has been the realization of a thorough study of the principles that govern its operation. Is remarkable that some of these principles have been recognized and characterized by our group. Other contributions of our research have been addressed to overcome some of the classical limitations of InI systems, like the limited depth of field (in pickup and in display), the poor axial and lateral resolution, the pseudoscopic-to-orthoscopic conversion, the production of 3Dimages with continuous relief, or the limited range of viewing angles of InI monitors.

The purpose of this study is to investigate a variational method for joint multiregion three-dimensional (3-D) motion segmentation and 3-D interpretation of temporal sequences of monocular images. Interpretation consists of dense recovery of 3-D structure and motion from the image sequence spatiotemporal variations due to short-range image motion. The method is direct insomuch as it does not require prior computation of image motion. It allows movement of both viewing system and multiple independently moving objects. The problem is formulated following a variational statement with a functional containing three terms. One term measures the conformity of the interpretation within each region of 3-D motion segmentation to the image sequence spatiotemporal variations. The second term is of regularization of depth. The assumption that environmental objects are rigid accounts automatically for the regularity of 3-D motion within each region of segmentation. The third and last term is for the regularity of segmentation boundaries. Minimization of the functional follows the corresponding Euler-Lagrange equations. This results in iterated concurrent computation of 3-D motion segmentation by curve evolution, depth by gradient descent, and 3-D motion by least squares within each region of segmentation. Curve evolution is implemented via level sets for topology independence and numerical stability. This algorithm and its implementation are verified on synthetic and real image sequences. Viewers presented with anaglyphs of stereoscopic images constructed from the algorithm's output reported a strong perception of depth. PMID:16519351

3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using a needle-like RF button electrode is widely used to destroy tumor cells or stop bleeding. To avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment, 3D US guidance system was developed. In this paper, a new automated technique, the 3D Improved Hough Transform (3DIHT) algorithm, which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance, was presented. Based on the coarse-fine search strategy and a four parameter representation of lines in 3D space, 3DIHT algorithm can segment needles quickly, accurately and robustly. The technique was evaluated using the 3D US images acquired by scanning a water phantom. The segmentation position deviation of the line was less than 2mm and angular deviation was much less than 2°. The average computational time measured on a Pentium IV 2.80GHz PC computer with a 381×381×250 image was less than 2s.

Recently developed interferometric 3Dimaging spectrometry (J. Opt. Soc. Am A18, 765 [2001]1084-7529JOAOD610.1364/JOSAA.18.000765) enables obtainment of the spectral information and 3D spatial information for incoherently illuminated or self-luminous object simultaneously. Using this method, we can obtain multispectral components of complex holograms, which correspond directly to the phase distribution of the wavefronts propagated from the polychromatic object. This paper focuses on the analysis of spectral resolution and 3D spatial resolution in interferometric 3Dimaging spectrometry. Our analysis is based on a novel analytical impulse response function defined over four-dimensional space. We found that the experimental results agree well with the theoretical prediction. This work also suggests a new criterion and estimate method regarding 3D spatial resolution of digital holography. PMID:27139648

The availability of 3D hardware has so far outpaced the production of 3D content. Although to date many methods have been proposed to convert 2D images to 3D stereopairs, the most successful ones involve human operators and, therefore, are time-consuming and costly, while the fully-automatic ones have not yet achieved the same level of quality. This subpar performance is due to the fact that automatic methods usually rely on assumptions about the captured 3D scene that are often violated in practice. In this paper, we explore a radically different approach inspired by our work on saliency detection in images. Instead of relying on a deterministic scene model for the input 2D image, we propose to "learn" the model from a large dictionary of stereopairs, such as YouTube 3D. Our new approach is built upon a key observation and an assumption. The key observation is that among millions of stereopairs available on-line, there likely exist many stereopairs whose 3D content matches that of the 2D input (query). We assume that two stereopairs whose left images are photometrically similar are likely to have similar disparity fields. Our approach first finds a number of on-line stereopairs whose left image is a close photometric match to the 2D query and then extracts depth information from these stereopairs. Since disparities for the selected stereopairs differ due to differences in underlying image content, level of noise, distortions, etc., we combine them by using the median. We apply the resulting median disparity field to the 2D query to obtain the corresponding right image, while handling occlusions and newly-exposed areas in the usual way. We have applied our method in two scenarios. First, we used YouTube 3D videos in search of the most similar frames. Then, we repeated the experiments on a small, but carefully-selected, dictionary of stereopairs closely matching the query. This, to a degree, emulates the results one would expect from the use of an extremely large 3D

The fabrication of a prosthetic socket for a below-the-knee amputee requires knowledge of the underlying bone structure in order to provide pressure relief for sensitive areas and support for load bearing areas. The goal is to enable the residual limb to bear pressure with greater ease and utility. Conventional methods of prosthesis fabrication are based on limited knowledge about the patient`s underlying bone structure. A 3D ultrasound imaging system was developed at Sandia National Laboratories. The imaging system provides information about the location of the bones in the residual limb along with the shape of the skin surface. Computer assisted design (CAD) software can use this data to design prosthetic sockets for amputees. Ultrasound was selected as the imaging modality. A computer model was developed to analyze the effect of the various scanning parameters and to assist in the design of the overall system. The 3D ultrasound imaging system combines off-the-shelf technology for image capturing, custom hardware, and control and image processing software to generate two types of image data -- volumetric and planar. Both volumetric and planar images reveal definition of skin and bone geometry with planar images providing details on muscle fascial planes, muscle/fat interfaces, and blood vessel definition. The 3D ultrasound imaging system was tested on 9 unilateral below-the- knee amputees. Image data was acquired from both the sound limb and the residual limb. The imaging system was operated in both volumetric and planar formats. An x-ray CT (Computed Tomography) scan was performed on each amputee for comparison. Results of the test indicate beneficial use of ultrasound to generate databases for fabrication of prostheses at a lower cost and with better initial fit as compared to manually fabricated prostheses.

We have developed semi-automated and fully-automated tools for the analysis of 3D single-photon emission computed tomography (SPECT) images. The focus is on the efficient boundary delineation of complex 3D structures that enables accurate measurement of their structural and physiologic properties. We employ intensity based thresholding algorithms for interactive and semi-automated analysis. We also explore fuzzy-connectedness concepts for fully automating the segmentation process. We apply the proposed tools to SPECT image data capturing variation of gastric accommodation and emptying. These image analysis tools were developed within the framework of a noninvasive scintigraphic test to measure simultaneously both gastric emptying and gastric volume after ingestion of a solid or a liquid meal. The clinical focus of the particular analysis was to probe associations between gastric accommodation/emptying and functional dyspepsia. Employing the proposed tools, we outline effectively the complex three dimensional gastric boundaries shown in the 3D SPECT images. We also perform accurate volume calculations in order to quantitatively assess the gastric mass variation. This analysis was performed both with the semi-automated and fully-automated tools. The results were validated against manual segmentation performed by a human expert. We believe that the development of an automated segmentation tool for SPECT imaging of the gastric volume variability will allow for other new applications of SPECT imaging where there is a need to evaluate complex organ function or tumor masses.

There are two main types of tomography that enable the 3D internal structures of objects to be reconstructed from scattered data. The commonly known computerized tomography (CT) give good results in the x-ray wavelength range where the filtered back-projection theorem and Radon transform can be used. These techniques rely on the Fourier projection-slice theorem where rays are considered to propagate straight through the object. Another type of tomography called `diffraction tomography' applies in applications in optics and acoustics where diffraction and scattering effects must be taken into account. The latter proves to be a more difficult problem, as light no longer travels straight through the sample. Holographic tomography is a popular way of performing diffraction tomography and there has been active experimental research on reconstructing complex refractive index data using this approach recently. However, there are two distinct ways of doing tomography: either by rotation of the object or by rotation of the illumination while fixing the detector. The difference between these two setups is intuitive but needs to be quantified. From Fourier optics and information transformation point of view, we use 3D transfer function analysis to quantitatively describe how spatial frequencies of the object are mapped to the Fourier domain. We first employ a paraxial treatment by calculating the Fourier transform of the defocused OTF. The shape of the calculated 3D CTF for tomography, by scanning the illumination in one direction only, takes on a form that we might call a 'peanut,' compared to the case of object rotation, where a diablo is formed, the peanut exhibiting significant differences and non-isotropy. In particular, there is a line singularity along one transverse direction. Under high numerical aperture conditions, the paraxial treatment is not accurate, and so we make use of 3D analytical geometry to calculate the behaviour in the non-paraxial case. This time, we

By real-time visual feedback of 3D scatter diagram of pulsatile tissue-motion, freehand ultrasonic diagnosis of neonatal ischemic diseases has been assisted at the bedside. The 2D ultrasonic movie was taken with a conventional ultrasonic apparatus (ATL HDI5000) and ultrasonic probes of 5-7 MHz with the compact tilt-sensor to measure the probe orientation. The real-time 3D visualization was realized by developing an extended version of the PC-based visualization system. The software was originally developed on the DirectX platform and optimized with the streaming SIMD extensions. The 3D scatter diagram of the latest pulsatile tissues has been continuously generated and visualized as projection image with the ultrasonic movie in the current section more than 15 fps. It revealed the 3D structure of pulsatile tissues such as middle and posterior cerebral arteries, Willis ring and cerebellar arteries, in which pediatricians have great interests in the blood flow because asphyxiated and/or low-birth-weight neonates have a high risk of ischemic diseases such as hypoxic-ischemic encephalopathy and periventricular leukomalacia. Since the pulsatile tissue-motion is due to local blood flow, it can be concluded that the system developed in this work is very useful to assist freehand ultrasonic diagnosis of ischemic diseases in the neonatal cranium.

Three-dimensional ultrasonicimaging, especially the emerging real-time version of it, is particularly valuable in medical applications such as echocardiography, obstetrics and surgical navigation. A known problem with ultrasound images is their high level of speckle noise. Anisotropic diffusion filtering has been shown to be effective in enhancing the visual quality of 3D ultrasound images and as preprocessing prior to advanced image processing. However, due to its arithmetic complexity and the sheer size of 3D ultrasound images, it is not possible to perform online, real-time anisotropic diffusion filtering using standard software implementations. We present an FPGA-based architecture that allows performing anisotropic diffusion filtering of 3Dimages at acquisition rates, thus enabling the use of this filtering technique in real-time applications, such as visualization, registration and volume rendering.

A complete 3-Dultrasonic pulsed Doppler system has been developed to measure quantitatively the velocity vector field of a fluid flow independently of the probe position. The probe consists of four 2.5 MHz piezocomposite ultrasonic transducers (one central transmitter and three receivers separated by 120 degrees ) to measure the velocity projections along three different directions. The Doppler shift of the three channels is calculated by analog phase and quadrature demodulation, then digitally processed to extract the mean velocity from the complex spectrum. The accuracy of the 3-D Doppler technique has been tested on a moving string phantom providing an error of about 4% for both amplitude and direction with an acquisition window of 100 ms. PMID:18238403

Light field optics and its applications become rather popular in these days. With light field optics or light field thesis, real 3D space can be described in 2D plane as 4D data, which we call as light field data. This process can be divided in two procedures. First, real3D scene is optically reduced with imaging lens. Second, this optically reduced 3Dimage is encoded into light field data. In later procedure we can say that 3D information is encoded onto a plane as 2D data by lens array plate. This transformation is reversible and acquired light field data can be decoded again into 3Dimage with the arrayed lens plate. "Refocusing" (focusing image on your favorite point after taking a picture), light-field camera's most popular function, is some kind of sectioning process from encoded 3D data (light field data) to 2D image. In this paper at first I show our actual light field camera and our 3D display using acquired and computer-simulated light field data, on which real 3Dimage is reconstructed. In second I explain our data processing method whose arithmetic operation is performed not in Fourier domain but in real domain. Then our 3D display system is characterized by a few features; reconstructed image is of finer resolutions than density of arrayed lenses and it is not necessary to adjust lens array plate to flat display on which light field data is displayed.

Three-dimensional (3D) information in a physical security system is a highly useful dis- criminator. The two-dimensional data from an imaging systems fails to provide target dis- tance and three-dimensional motion vector, which can be used to reduce nuisance alarm rates and increase system effectiveness. However, 3Dimaging devices designed primarily for use in physical security systems are uncommon. This report discusses an architecture favorable to physical security systems; an inexpensive snapshot 3Dimaging system utilizing a simple illumination system. The method of acquiring 3D data, tests to understand illumination de- sign, and software modifications possible to maximize information gathering capability are discussed.

A full 3D quasi-holographic image processing technique developed by ONERA is described. A complex backscattering coefficient of a drone scale model was measured for discrete values of the 3D backscattered wave vector in a frequency range between 4.5-8 GHz. The 3Dimage processing is implemented on a HP 1000 mini-computer and will be part of LASER 2 software to be used in three RCS measurement indoor facilities.

A volumetric image display is a new display technology capable of displaying computer generated 3Dimages in a volumetric space. Many viewers can walk around the display and see the image from omni-directions simultaneously without wearing any glasses. The image is real and possesses all major elements in both physiological and psychological depth cues. Due to the volumetric nature of its image, the VID can provide the most natural human-machine interface in operations involving 3D data manipulation and 3D targets monitoring. The technology creates volumetric 3Dimages by projecting a series of profiling images distributed in the space form a volumetric image because of the after-image effect of human eyes. Exemplary applications in biomedical image visualization were tested on a prototype display, using different methods to display a data set from Ct-scans. The features of this display technology make it most suitable for applications that require quick understanding of the 3D relations, need frequent spatial interactions with the 3Dimages, or involve time-varying 3D data. It can also be useful for group discussion and decision making.

In the eighteenth century, techniques that enabled a strong sense of 3D perception to be experienced without recourse to binocular disparities (arising from the spatial separation of the eyes) underpinned the first significant commercial sales of 3D viewing devices and associated content. However following the advent of stereoscopic techniques in the nineteenth century, 3Dimage depiction has become inextricably linked to binocular parallax and outside the vision science and arts communities relatively little attention has been directed towards earlier approaches. Here we introduce relevant concepts and terminology and consider a number of techniques and optical devices that enable 3D perception to be experienced on the basis of planar images rendered from a single vantage point. Subsequently we allude to possible mechanisms for non-binocular parallax based 3D perception. Particular attention is given to reviewing areas likely to be thought-provoking to those involved in 3D display development, spatial visualization, HCI, and other related areas of interdisciplinary research.

In this paper, a three-dimensional (3D) integral imaging display for augmented reality is presented. By implementing the pseudoscopic-to-orthoscopic conversion method, elemental image arrays with different capturing parameters can be transferred into the identical format for 3D display. With the proposed merging algorithm, a new set of elemental images for augmented reality display is generated. The newly generated elemental images contain both the virtual objects and real world scene with desired depth information and transparency parameters. The experimental results indicate the feasibility of the proposed 3D augmented reality with integral imaging.

Surface topography is an important variable in the performance of many industrial components and is normally measured with diamond-tip profilometry over a small area or using optical scattering methods for larger area measurement. This article shows quantitative surface topography profiles as obtained using only high-frequency focused air-coupled ultrasonic pulses. The profiles were obtained using a profiling system developed by NASA Glenn Research Center and Sonix, Inc (via a formal cooperative agreement). (The air transducers are available as off-the-shelf items from several companies.) The method is simple and reproducible because it relies mainly on knowledge and constancy of the sound velocity through the air. The air transducer is scanned across the surface and sends pulses to the sample surface where they are reflected back from the surface along the same path as the incident wave. Time-of-flight images of the sample surface are acquired and converted to depth/surface profile images using the simple relation (d = V*t/2) between distance (d), time-of-flight (t), and the velocity of sound in air (V). The system has the ability to resolve surface depression variations as small as 25 microns, is useable over a 1.4 mm vertical depth range, and can profile large areas only limited by the scan limits of the particular ultrasonic system. (Best-case depth resolution is 0.25 microns which may be achievable with improved isolation from vibration and air currents.) The method using an optimized configuration is reasonably rapid and has all quantitative analysis facilities on-line including 2-D and 3-D visualization capability, extreme value filtering (for faulty data), and leveling capability. Air-coupled surface profilometry is applicable to plate-like and curved samples. In this article, results are shown for several proof-of-concept samples, plastic samples burned in microgravity on the STS-54 space shuttle mission, and a partially-coated cylindrical ceramic

This paper proposes a novel recognition scheme algorithm for semantic labeling of 2D object present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to infer the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Results obtained show promising performances, with recognition rate up to 84%, which opens interesting perspectives in terms of semantic metadata extraction from still images/videos.

Cells in higher organisms naturally exist in a three dimensional (3D) structure, a fact sometimes ignored by in vitro biological research. Confinement to a two dimensional culture imposes significant deviations from the native 3D state. One of the biggest obstacles to wider use of 3D cultures is the difficulty of 3Dimaging. The confocal microscope, the dominant 3Dimaging instrument, is expensive, bulky, and light-intensive; live cells can be observed for only a short time before they suffer photodamage. We present an alternative 3Dimaging techinque, digital holographic microscopy, which can capture 3D information with axial resolution better than 2 μm in a 100 μm deep volume. Capturing a 3Dimage requires only a single camera exposure with a sub-millisecond laser pulse, allowing us to image cell cultures using five orders of magnitude less light energy than with confocal. This can be done with hardware costing ~ 1000. We use the instrument to image growth of MCF7 breast cancer cells and p. pastoras yeast. We acknowledge support from NSF GRFP.

An instrument capable of highly accurate, non-contact range measurement has been developed, which is based upon the principle of projected rotating fringes. More usually known as dynamic fringe projection, it is this technique which is exploited in the dynamic automated range transducer (DART). The intensity waveform seen at the target and sensed by the detector, contains all the information required to accurately determine the fringe order. This, in turn, allows the range to be evaluated by the substitution of the fringe order into a simple algebraic expression. Various techniques for the analysis of the received intensity signals from the surface of the target have been investigated. The accuracy to which the range can be determined ultimately depends upon the accuracy to which the fringe order can be evaluated from the received intensity waveform. It is extremely important to be able to closely determine the fractional fringe order value, to achieve any meaningful results. This paper describes a number of techniques which have been used to analyze the intensity waveform, and critically appraises their suitability in terms of accuracy and required speed of operation. This work also examines the development of this instrument for three-dimensional measurements based on single or two beam systems. Using CCD array detectors, a 3-D range map of the object's surface may be produced.

Purpose: The objective is to develop a multivariate in vivo hemodynamic model of tissue oxygenation (MiHMO2) based on 3D photoacoustic spectroscopy. Introduction: Low oxygen levels, or hypoxia, deprives cancer cells of oxygen and confers resistance to irradiation, some chemotherapeutic drugs, and oxygen-dependent therapies (phototherapy) leading to treatment failure and poor disease-free and overall survival. For example, clinical studies of patients with breast carcinomas, cervical cancer, and head and neck carcinomas (HNC) are more likely to suffer local reoccurrence and metastasis if their tumors are hypoxic. A novel method to non invasively measure tumor hypoxia, identify its type, and monitor its heterogeneity is devised by measuring tumor hemodynamics, MiHMO2. Material and Methods: Simulations are performed to compare tumor pO2 levels and hypoxia based on physiology - perfusion, fractional plasma volume, fractional cellular volume - and its hemoglobin status - oxygen saturation and hemoglobin concentration - based on in vivo measurements of breast, prostate, and ovarian tumors. Simulations of MiHMO2 are performed to assess the influence of scanner resolutions and different mathematic models of oxygen delivery. Results: Sensitivity of pO2 and hypoxic fraction to photoacoustic scanner resolution and dependencies on model complexity will be presented using hemodynamic parameters for different tumors. Conclusions: Photoacoustic CT spectroscopy provides a unique ability to monitor hemodynamic and cellular physiology in tissue, which can be used to longitudinally monitor tumor oxygenation and its response to anti-angiogenic therapies.

We present a new method of highway 3-D model construction developed based on feature extraction in highway images and LIDAR data. We describe the processing road coordinate data that connect the image frames to the coordinates of the elevation data. Image processing methods are used to extract sky, road, and ground regions as well as significant objects (such as signs and building fronts) in the roadside for the 3D model. LIDAR data are interpolated and processed to extract the road lanes as well as other features such as trees, ditches, and elevated objects to form the 3D model. 3D geometry reasoning is used to match the image features to the 3D model. Results from successive frames are integrated to improve the final model.

This paper presents a wavelet-based lossy compression technique for unidirectional 3D integral images (UII). The method requires the extraction of different viewpoint images from the integral image. A single viewpoint image is constructed by extracting one pixel from each microlens, then each viewpoint image is decomposed using a Two Dimensional Discrete Wavelet Transform (2D-DWT). The resulting array of coefficients contains several frequency bands. The lower frequency bands of the viewpoint images are assembled and compressed using a 3 Dimensional Discrete Cosine Transform (3D-DCT) followed by Huffman coding. This will achieve decorrelation within and between 2D low frequency bands from the different viewpoint images. The remaining higher frequency bands are Arithmetic coded. After decoding and decompression of the viewpoint images using an inverse 3D-DCT and an inverse 2D-DWT, each pixel from every reconstructed viewpoint image is put back into its original position within the microlens to reconstruct the whole 3D integral image. Simulations were performed on a set of four different grey level 3D UII using a uniform scalar quantizer with deadzone. The results for the average of the four UII intensity distributions are presented and compared with previous use of 3D-DCT scheme. It was found that the algorithm achieves better rate-distortion performance, with respect to compression ratio and image quality at very low bit rates.

A method is proposed to compute and synthesize the microrelief of a diffractive optical element to produce a new visual security feature - the vertical 3D/3D switch effect. The security feature consists in the alternation of two 3D color images when the diffractive element is tilted up/down. Optical security elements that produce the new security feature are synthesized using electron-beam technology. Sample optical security elements are manufactured that produce 3D to 3D visual switch effect when illuminated by white light. Photos and video records of the vertical 3D/3D switch effect of real optical elements are presented. The optical elements developed can be replicated using standard equipment employed for manufacturing security holograms. The new optical security feature is easy to control visually, safely protected against counterfeit, and designed to protect banknotes, documents, ID cards, etc. PMID:27137530

With the development of virtual reality, there is a growing demand for 3D modeling of real scenes. This paper proposes a novel 3D scene reconstruction framework based on multi-aperture images. Our framework consists of four parts. Firstly, images with different apertures are captured via programmable aperture. Secondly, we use SIFT method for feature point matching. Then we exploit binocular stereo vision to calculate camera parameters and 3D positions of matching points, forming a sparse 3D scene model. Finally, we apply patch-based multi-view stereo to obtain a dense 3D scene model. Experimental results show that our method is practical and effective to reconstruct dense 3D scene.

Purpose: To report the design and imaging methodology of a photoacoustic scanner dedicated to imaging hemoglobin distribution throughout a human breast. Methods: The authors developed a dedicated breast photoacoustic mammography (PAM) system using a spherical detector aperture based on our previous photoacoustic tomography scanner. The system uses 512 detectors with rectilinear scanning. The scan shape is a spiral pattern whose radius varies from 24 to 96 mm, thereby allowing a field of view that accommodates a wide range of breast sizes. The authors measured the contrast-to-noise ratio (CNR) using a target comprised of 1-mm dots printed on clear plastic. Each dot absorption coefficient was approximately the same as a 1-mm thickness of whole blood at 756 nm, the output wavelength of the Alexandrite laser used by this imaging system. The target was immersed in varying depths of an 8% solution of stock Liposyn II-20%, which mimics the attenuation of breast tissue (1.1 cm−1). The spatial resolution was measured using a 6 μm-diameter carbon fiber embedded in agar. The breasts of four healthy female volunteers, spanning a range of breast size from a brassiere C cup to a DD cup, were imaged using a 96-mm spiral protocol. Results: The CNR target was clearly visualized to a depth of 53 mm. Spatial resolution, which was estimated from the full width at half-maximum of a profile across the PAM image of a carbon fiber, was 0.42 mm. In the four human volunteers, the vasculature was well visualized throughout the breast tissue, including to the chest wall. Conclusions: CNR, lateral field-of-view and penetration depth of our dedicated PAM scanning system is sufficient to image breasts as large as 1335 mL, which should accommodate up to 90% of the women in the United States. PMID:24320471

We present three codes for the Intel Paragon that address the problem of three-dimensional seismic imaging of complex geologies. The first code models acoustic wave propagation and can be used to generate data sets to calibrate and validate seismic imaging codes. This code reported the fastest timings for acoustic wave propagation codes at a recent SEG (Society of Exploration Geophysicists) meeting. The second code implements a Kirchhoff method for pre-stack depth migration. Development of this code is almost complete, and preliminary results are presented. The third code implements a wave equation approach to seismic migration and is a Paragon implementation of a code from the ARCO Seismic Benchmark Suite.

A three-dimensional capacitance density imaging of a gasified bed or the like in a containment vessel is achieved using a plurality of electrodes provided circumferentially about the bed in levels and along the bed in channels. The electrodes are individually and selectively excited electrically at each level to produce a plurality of current flux field patterns generated in the bed at each level. The current flux field patterns are suitably sensed and a density pattern of the bed at each level determined. By combining the determined density patterns at each level, a three-dimensional density image of the bed is achieved. 7 figs.

We develop a method for obtaining 3D polarimetric integral images from elemental images recorded in low light illumination conditions. Since photon-counting images are very sparse, calculation of the Stokes parameters and the degree of polarization should be handled carefully. In our approach, polarimetric 3D integral images are generated using the Maximum Likelihood Estimation and subsequently reconstructed by means of a Total Variation Denoising filter. In this way, polarimetric results are comparable to those obtained in conventional illumination conditions. We also show that polarimetric information retrieved from photon starved images can be used in 3D object recognition problems. To the best of our knowledge, this is the first report on 3D polarimetric photon counting integral imaging. PMID:25836861

The O-arm (Medtronic Inc.) is a multi-dimensional surgical imaging platform. The purpose of this study was to perform a quantitative evaluation of the imaging performance of the O-arm in an effort to understand its potential for future nonorthopedic applications. Performance of the reconstructed 3Dimages was evaluated, using a custom-built phantom, in terms of resolution, linearity, uniformity and geometrical accuracy. Both the standard (SD, 13 s) and high definition (HD, 26 s) modes were evaluated, with the imaging parameters set to image the head (120 kVp, 100 mAs and 150 mAs, respectively). For quantitative noise characterization, the images were converted to Hounsfield units (HU) off-line. Measurement of the modulation transfer function revealed a limiting resolution (at 10% level) of 1.0 mm-1 in the axial dimension. Image noise varied between 15 and 19 HU for the HD and SD modes, respectively. Image intensities varied linearly over the measured range, up to 1300 HU. Geometric accuracy was maintained in all three dimensions over the field of view. The present study has evaluated the performance characteristics of the O-arm, and demonstrates feasibility for use in interventional applications and quantitative imaging tasks outside those currently targeted by the manufacturer. Further improvements to the reconstruction algorithms may further enhance performance for lower-contrast applications.

Locating specific 3D objects in overhead images is an important problem in many remote sensing applications. 3D objects may contain either one connected component or multiple disconnected components. Solutions must accommodate images acquired with diverse sensors at various times of the day, in various seasons of the year, or under various weather conditions. Moreover, the physical manifestation of a 3D object with fixed physical dimensions in an overhead image is highly dependent on object physical dimensions, object position/orientation, image spatial resolution, and imaging geometry (e.g., obliqueness). This paper describes a two-stage computer-assisted approach for locating 3D objects in overhead images. In the matching stage, the computer matches models of 3D objects to overhead images. The strongest degree of match over all object orientations is computed at each pixel. Unambiguous local maxima in the degree of match as a function of pixel location are then found. In the cueing stage, the computer sorts image thumbnails in descending order of figure-of-merit and presents them to human analysts for visual inspection and interpretation. The figure-of-merit associated with an image thumbnail is computed from the degrees of match to a 3D object model associated with unambiguous local maxima that lie within the thumbnail. This form of computer assistance is invaluable when most of the relevant thumbnails are highly ranked, and the amount of inspection time needed is much less for the highly ranked thumbnails than for images as a whole.

This paper deals with new optical non-conventional 3D laser imaging. Optical non-conventional imaging explores the advantages of laser imaging to form a three-dimensional image of the scene. 3D laser imaging can be used for threedimensional medical imaging, topography, surveillance, robotic vision because of ability to detect and recognize objects. In this paper, we present a 3D laser imaging for concealed object identification. The objective of this new 3D laser imaging is to provide the user a complete 3D reconstruction of the concealed object from available 2D data limited in number and with low representativeness. The 2D laser data used in this paper come from simulations that are based on the calculation of the laser interactions with the different interfaces of the scene of interest and from experimental results. We show the global 3D reconstruction procedures capable to separate objects from foliage and reconstruct a threedimensional image of the considered object. In this paper, we present examples of reconstruction and completion of three-dimensional images and we analyse the different parameters of the identification process such as resolution, the scenario of camouflage, noise impact and lacunarity degree.

Objective Conventional inverse-scattering algorithms for microwave breast imaging result in moderate resolution images with blurred boundaries between tissues. Recent 2D numerical microwave imaging studies demonstrate that the use of a level set method preserves dielectric boundaries, resulting in a more accurate, higher resolution reconstruction of the dielectric properties distribution. Previously proposed level set algorithms are computationally expensive and thus impractical in 3D. In this paper we present a computationally tractable 3D microwave imaging algorithm based on level sets. Methods We reduce the computational cost of the level set method using a Jacobian matrix, rather than an adjoint method, to calculate Frechet derivatives. We demonstrate the feasibility of 3Dimaging using simulated array measurements from 3D numerical breast phantoms. We evaluate performance by comparing full 3D reconstructions to those from a conventional microwave imaging technique. We also quantitatively assess the efficacy of our algorithm in evaluating breast density. Results Our reconstructions of 3D numerical breast phantoms improve upon those of a conventional microwave imaging technique. The density estimates from our level set algorithm are more accurate than those of conventional microwave imaging, and the accuracy is greater than that reported for mammographic density estimation. Conclusion Our level set method leads to a feasible level of computational complexity for full 3Dimaging, and reconstructs the heterogeneous dielectric properties distribution of the breast more accurately than conventional microwave imaging methods. Significance 3D microwave breast imaging using a level set method is a promising low-cost, non-ionizing alternative to current breast imaging techniques. PMID:26011863

Purpose: The authors aim to improve image guidance during percutaneous coronary interventions of chronic total occlusions (CTO) by providing information obtained from computed tomography angiography (CTA) to the cardiac interventionist. To this end, the authors investigate a method to register a 3D CTA model to biplane reconstructions. Methods: The authors developed a method for registering preoperative coronary CTA with intraoperative biplane x-ray angiography (XA) images via 3D models of the coronary arteries. The models are extracted from the CTA and biplane XA images, and are temporally aligned based on CTA reconstruction phase and XA ECG signals. Rigid spatial alignment is achieved with a robust probabilistic point set registration approach using Gaussian mixture models (GMMs). This approach is extended by including orientation in the Gaussian mixtures and by weighting bifurcation points. The method is evaluated on retrospectively acquired coronary CTA datasets of 23 CTO patients for which biplane XA images are available. Results: The Gaussian mixture model approach achieved a median registration accuracy of 1.7 mm. The extended GMM approach including orientation was not significantly different (P > 0.1) but did improve robustness with regards to the initialization of the 3D models. Conclusions: The authors demonstrated that the GMM approach can effectively be applied to register CTA to biplane XA images for the purpose of improving image guidance in percutaneous coronary interventions.

Currently three imaging spectrometer architectures, tunable filter, dispersive, and Fourier transform, are viable for imaging the universe in three dimensions. There are domains of greatest utility for each of these architectures. The optimum choice among the various alternative architectures is dependent on the nature of the desired observations, the maturity of the relevant technology, and the character of the backgrounds. The domain appropriate for each of the alternatives is delineated; both for instruments having ideal performance as well as for instrumentation based on currently available technology. The environment and science objectives for the Next Generation Space Telescope will be used as a specific representative case to provide a basis for comparison of the various alternatives.

Targeted radionuclide therapy holds promise as a new treatment against cancer. Advances in imaging are making it possible to evaluate the spatial distribution of radioactivity in tumors and normal organs over time. Matched anatomical imaging such as combined SPECT/CT and PET/CT have also made it possible to obtain tissue density information in conjunction with the radioactivity distribution. Coupled with sophisticated iterative reconstruction algorithims, these advances have made it possible to perform highly patient-specific dosimetry that also incorporates radiobiological modeling. Such sophisticated dosimetry techniques are still in the research investigation phase. Given the attendant logistical and financial costs, a demonstrated improvement in patient care will be a prerequisite for the adoption of such highly-patient specific internal dosimetry methods. PMID:18662554

Our goals for the first year of this three dimensional electodynamic imaging project was to determine how to combine flexible, individual addressable; preprocessing of array source signals; spectral extrapolation or received signals; acoustic tomography codes; and acoustic propagation modeling code. We investigated flexible, individually addressable acoustic array material to find the best match in power, sensitivity and cost and settled on PVDF sheet arrays and 3-1 composite material.

Three-dimensional (3D) modeling of medical images is a critical part of surgical simulation. In this paper, we focus on the magnetic resonance (MR) images denoising for brain modeling reconstruction, and exploit a practical solution. We attempt to remove the noise existing in the MR imaging signal and preserve the image characteristics. A wavelet-based adaptive curve shrinkage function is presented in spherical coordinates system. The comparative experiments show that the denoising method can preserve better image details and enhance the coefficients of contours. Using these denoised images, the brain 3D visualization is given through surface triangle mesh model, which demonstrates the effectiveness of the proposed method.

We present a proof-of-concept experiment utilizing a novel "snap-shot" spectral domain OCT technique that captures a phase coherent volume in a single frame. The sample is illuminated with a collimated beam of 75 μm diameter and the back-reflected light is analyzed by a 2-D matrix of spectral interferograms. A key challenge that is addressed is simultaneously maintaining lateral and spectral phase coherence over the imaged volume in the presence of sample motion. Digital focusing is demonstrated for 5.0 μm lateral resolution over an 800 μm axial range.

Recent studies have shown how volumetric imaging and morphometrics can add significantly to our understanding of morphogenesis, the developmental basis for variation, and the etiology of structural birth defects. On the other hand, the complex questions and diverse imaging data in developmental biology present morphometrics with more complex challenges than applications in virtually any other field. Meeting these challenges is necessary in order to understand the mechanistic basis for variation in complex morphologies. This chapter reviews the methods and theory that enable the application of modern landmark-based morphometrics to developmental biology and craniofacial development, in particular. We discuss the theoretical foundations of morphometrics as applied to development and review the basic approaches to the quantification of morphology. Focusing on geometric morphometrics, we discuss the principal statistical methods for quantifying and comparing morphological variation and covariation structure within and among groups. Finally, we discuss the future directions for morphometrics in developmental biology that will be required for approaches that enable quantitative integration across the genotype-phenotype map. PMID:26589938

White-light diffraction tomography (WDT) is a recently developed 3Dimaging technique based on a quantitative phase imaging system called spatial light interference microscopy (SLIM). The technique has achieved a sub-micron resolution in all three directions with high sensitivity granted by the low-coherence of a white-light source. Demonstrations of the technique on single cell imaging have been presented previously; however, imaging on any larger sample, including a cluster of cells, has not been demonstrated using the technique. Neurons in an animal body form a highly complex and spatially organized 3D structure, which can be characterized by neuronal networks or circuits. Currently, the most common method of studying the 3D structure of neuron networks is by using a confocal fluorescence microscope, which requires fluorescence tagging with either transient membrane dyes or after fixation of the cells. Therefore, studies on neurons are often limited to samples that are chemically treated and/or dead. WDT presents a solution for imaging live neuron networks with a high spatial and temporal resolution, because it is a 3Dimaging method that is label-free and non-invasive. Using this method, a mouse or rat hippocampal neuron culture and a mouse dorsal root ganglion (DRG) neuron culture have been imaged in order to see the extension of processes between the cells in 3D. Furthermore, the tomogram is compared with a confocal fluorescence image in order to investigate the 3D structure at synapses.

We measured accommodation responses under integral photography (IP), binocular stereoscopic, and real object display conditions, and viewing conditions of binocular and monocular viewing conditions. The equipment we used was an optometric device and a 3D display. We developed the 3D display for IP and binocular stereoscopic images that comprises a high-resolution liquid crystal display (LCD) and a high-density lens array. The LCD has a resolution of 468 dpi and a diagonal size of 4.8 inches. The high-density lens array comprises 106 x 69 micro lenses that have a focal length of 3 mm and diameter of 1 mm. The lenses are arranged in a honeycomb pattern. The 3D display was positioned 60 cm from an observer under IP and binocular stereoscopic display conditions. The target was presented at eight depth positions relative to the 3D display: 15, 10, and 5 cm in front of the 3D display, on the 3D display panel, and 5, 10, 15 and 30 cm behind the 3D display under the IP and binocular stereoscopic display conditions. Under the real object display condition, the target was displayed on the 3D display panel, and the 3D display was placed at the eight positions. The results suggest that the IP image induced more natural accommodation responses compared to the binocular stereoscopic image. The accommodation responses of the IP image were weaker than those of a real object; however, they showed a similar tendency with those of the real object under the two viewing conditions. Therefore, IP can induce accommodation to the depth positions of 3Dimages.

A total laryngectomy removes the vocal folds which are fundamental in forming voiced sounds that make speech possible. Although implanted prosthetics are commonly used in developed countries, simple handheld vibrating electrolarynxes are still common worldwide. These devices are easy to use but suffer from many drawbacks including dedication of a hand, mechanical sounding voice, and sound leakage. To address some of these drawbacks, we introduce a novel electrolarynx that uses vibro-acoustic interference of dual ultrasonic waves to generate an audible fundamental frequency. A 3D simulation of the principles of the device is presented in this paper. PMID:25401965

3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India). This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can't do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good result. For Large city

Significant advances in structural analysis of deep water structure, salt tectonic and extensional rift basin come from the descriptions of fault system geometries imaged in 3D seismic data. However, even where seismic data are excellent, in most cases the trajectory of thrust faults is highly conjectural and still significant uncertainty exists as to the patterns of deformation that develop between the main faults segments, and even of the fault architectures themselves. Moreover structural interpretations that conventionally define faults by breaks and apparent offsets of seismic reflectors are commonly conditioned by a narrow range of theoretical models of fault behavior. For example, almost all interpretations of thrust geometries on seismic data rely on theoretical "end-member" behaviors where concepts as strain localization or multilayer mechanics are simply avoided. Yet analogue outcrop studies confirm that such descriptions are commonly unsatisfactory and incomplete. In order to fill these gaps and improve the 3D visualization of deformation in the subsurface, seismic attribute methods are developed here in conjunction with conventional mapping of reflector amplitudes (Marfurt & Chopra, 2007)). These signal processing techniques recently developed and applied especially by the oil industry use variations in the amplitude and phase of the seismic wavelet. These seismic attributes improve the signal interpretation and are calculated and applied to the entire 3D seismic dataset. In this contribution we will show 3D seismic examples of fault structures from gravity-driven deep-water thrust structures and extensional basin systems to indicate how 3D seismic image processing methods can not only build better the geometrical interpretations of the faults but also begin to map both strain and damage through amplitude/phase properties of the seismic signal. This is done by quantifying and delineating the short-range anomalies on the intensity of reflector amplitudes

Region of interest (ROI) of a medical image is an area including important diagnostic information and must be stored without any distortion. This algorithm for application of watermarking technique for non-ROI of the medical image preserving ROI. The paper presents a 3D watermark based medical image watermarking scheme. In this paper, a 3D watermark object is first decomposed into 2D elemental image array (EIA) by a lenslet array, and then the 2D elemental image array data is embedded into the host image. The watermark extraction process is an inverse process of embedding. The extracted EIA through the computational integral imaging reconstruction (CIIR) technique, the 3D watermark can be reconstructed. Because the EIA is composed of a number of elemental images possesses their own perspectives of a 3D watermark object. Even though the embedded watermark data badly damaged, the 3D virtual watermark can be successfully reconstructed. Furthermore, using CAT with various rule number parameters, it is possible to get many channels for embedding. So our method can recover the weak point having only one transform plane in traditional watermarking methods. The effectiveness of the proposed watermarking scheme is demonstrated with the aid of experimental results.

Ultrasonic techniques, such as the use of guided waves, can be ideal for finding damage in the plate and pipe-like structures used in aerospace applications. However, the interaction of waves with real flaw types and geometries can lead to experimental signals that are difficult to interpret. 3-dimensional (3D) elastic wave simulations can be a powerful tool in understanding the complicated wave scattering involved in flaw detection and for optimizing experimental techniques. We have developed and implemented parallel 3D elastodynamic finite integration technique (3D EFIT) code to investigate Lamb wave scattering from realistic flaws. This paper discusses simulation results for an aluminum-aluminum diffusion disbond and an aluminum-epoxy disbond and compares results from the disbond case to the common artificial flaw type of a flat-bottom hole. The paper also discusses the potential for extending the 3D EFIT equations to incorporate physics-based weak bond models for simulating wave scattering from weak adhesive bonds.

Ultrasonic techniques, such as the use of guided waves, can be ideal for finding damage in the plate and pipe-like structures used in aerospace applications. However, the interaction of waves with real flaw types and geometries can lead to experimental signals that are difficult to interpret. 3-dimensional (3D) elastic wave simulations can be a powerful tool in understanding the complicated wave scattering involved in flaw detection and for optimizing experimental techniques. We have developed and implemented parallel 3D elastodynamic finite integration technique (3D EFIT) code to investigate Lamb wave scattering from realistic flaws. This paper discusses simulation results for an aluminum-aluminum diffusion disbond and an aluminum-epoxy disbond and compares results from the disbond case to the common artificial flaw type of a flat-bottom hole. The paper also discusses the potential for extending the 3D EFIT equations to incorporate physics-based weak bond models for simulating wave scattering from weak adhesive bonds.

Aperture Synthesis Imaging Radar (ASIR) is one of the technologies adopted by the EISCAT_3D project to endow it with imaging capabilities in 3-dimensions that includes sub-beam resolution. Complemented by pulse compression, it will provide 3-dimensional images of certain types of incoherent scatter radar targets resolved to about 100 metres at 100 km range, depending on the signal-to-noise ratio. This ability will open new research opportunities to map small structures associated with non-homogeneous, unstable processes such as aurora, summer and winter polar radar echoes (PMSE and PMWE), Natural Enhanced Ion Acoustic Lines (NEIALs), structures excited by HF ionospheric heating, meteors, space debris, and others. The underlying physico-mathematical principles of the technique are the same as the technique employed in radioastronomy to image stellar objects; both require sophisticated inversion techniques to obtain reliable images.

The two major volume visualization methods used in biomedical applications are Maximum Intensity Projection (MIP) and Volume Rendering (VR), both of which involve the process of creating sets of 2D projections from 3Dimages. We have developed a new method for very fast, high-quality volume visualization of 3D biomedical images, based on the fact that the inverse of this process (transforming 2D projections into a 3Dimage) is essentially equivalent to tomographic image reconstruction. This new method uses the 2D projections acquired by the scanner, thereby obviating the need for the two computationally expensive steps currently required in the complete process of biomedical visualization, that is, (i) reconstructing the 3Dimage from 2D projection data, and (ii) computing the set of 2D projections from the reconstructed 3Dimage As well as improvements in computation speed, this method also results in improvements in visualization quality, and in the case of x-ray CT we can exploit this quality improvement to reduce radiation dosage. In this paper, demonstrate the benefits of developing biomedical visualization techniques by directly processing the sensor data acquired by body scanners, rather than by processing the image data reconstructed from the sensor data. We show results of using this approach for volume visualization for tomographic modalities, like x-ray CT, and as well as for MRI.

Spot welds are used to join sheets of metals in the automotive industry. When spot weld quality is evaluated using conventional ultrasonic manual pulse-echo method, the reliability of the inspection is affected by selection of the probe diameter and the positioning of the probe in the weld center. The application of a 2D matrix array is a potential solution to the aforementioned problems. The objective of this work was to develop a signal processing algorithm to reconstruct the 3D spot weld volume showing the size of the nugget and the defects in it. In order to achieve this, the conventional total focusing method was enhanced by taking into account the directivities of the single elements of the array and the divergence of the ultrasonic beam due to the propagation distance. Enhancements enabled a reduction in the background noise and uniform sensitivity at different depths to be obtained. The proposed algorithm was verified using a finite element model of ultrasonic wave propagation simulating three common spot weld conditions: a good weld, an undersized weld, and a weld containing a pore. The investigations have demonstrated that proposed method enables the determination of the size of the nugget and detection of discontinuities.

We develop a 3D thermography imaging standardization technique to allow quantitative data analysis. Medical Digital Infrared Thermal Imaging is very sensitive and reliable mean of graphically mapping and display skin surface temperature. It allows doctors to visualise in colour and quantify temperature changes in skin surface. The spectrum of colours indicates both hot and cold responses which may co-exist if the pain associate with an inflammatory focus excites an increase in sympathetic activity. However, due to thermograph provides only qualitative diagnosis information, it has not gained acceptance in the medical and veterinary communities as a necessary or effective tool in inflammation and tumor detection. Here, our technique is based on the combination of visual 3Dimaging technique and thermal imaging technique, which maps the 2D thermography images on to 3D anatomical model. Then we rectify the 3D thermogram into a view independent thermogram and conform it a standard shape template. The combination of these imaging facilities allows the generation of combined 3D and thermal data from which thermal signatures can be quantified.

In conventional 3D Fourier transform (3DFT) MR imaging, signal-to-noise ratio (SNR) is governed by the well-known relationship of being proportional to the voxel size and square root of the imaging time. Here, we introduce an alternative 3Dimaging approach, termed MRT (Magnetic Resonance Tomosynthesis), which can generate a set of tomographic MR images similar to multiple 2D projection images in x-ray. A multiple-oblique-view (MOV) pulse sequence is designed to acquire the tomography-like images used in tomosynthesis process and an iterative back-projection (IBP) reconstruction method is used to reconstruct 3Dimages. SNR analysis is performed and shows that resolution and SNR tradeoff is not governed as with typical 3DFT MR imaging case. The proposed method provides a higher SNR than the conventional 3Dimaging method with a partial loss of slice-direction resolution. It is expected that this method can be useful for extremely low SNR cases.

In this research, the recognition of gesture in 3D space is examined by using serial range images obtained by a real-time 3D measurement system developed in our laboratory. Using this system, it is possible to obtain time sequences of range, intensity and color data for a moving object in real-time without assigning markers to the targets. At first, gestures are tracked in 2D space by calculating 2D flow vectors at each points using an ordinal optical flow estimation method, based on time sequences of the intensity data. Then, location of each point after 2D movement is detected on the x-y plane using thus obtained 2D flow vectors. Depth information of each point after movement is then obtained from the range data and 3D flow vectors are assigned to each point. Time sequences of thus obtained 3D flow vectors allow us to track the 3D movement of the target. So, based on time sequences of 3D flow vectors of the targets, it is possible to classify the movement of the targets using continuous DP matching technique. This tracking of 3D movement using time sequences of 3D flow vectors may be applicable for a robust gesture recognition system.

The increasing prevalence of obesity suggests a need to develop a convenient, reliable and economical tool for assessment of this condition. Three-dimensional (3D) body surface imaging has emerged as an exciting technology for estimation of body composition. This paper presents a new 3D body imaging system, which was designed for enhanced portability, affordability, and functionality. In this system, stereo vision technology was used to satisfy the requirements for a simple hardware setup and fast image acquisitions. The portability of the system was created via a two-stand configuration, and the accuracy of body volume measurements was improved by customizing stereo matching and surface reconstruction algorithms that target specific problems in 3D body imaging. Body measurement functions dedicated to body composition assessment also were developed. The overall performance of the system was evaluated in human subjects by comparison to other conventional anthropometric methods, as well as air displacement plethysmography, for body fat assessment.

Three-dimensional displays are used extensively in movies and games. These displays are also essential in mixed reality, where virtual and real spaces overlap. Therefore, engineers and creators should be trained to master 3D display technologies. For this reason, the Department of Information Media at the Kanagawa Institute of Technology has launched two 3Dimage display courses specifically designed for students who aim to become information media engineers and creators. PMID:26960028

Medical image segmentation is the process that defines the region of interest in the image volume. Classical segmentation methods such as region-based methods and boundary-based methods cannot make full use of the information provided by the image. In this paper we proposed a general hybrid framework for 3D medical image segmentation purposes. In our approach we combine the Gibbs Prior model, and the deformable model. First, Gibbs Prior models are applied onto each slice in a 3D medical image volume and the segmentation results are combined to a 3D binary masks of the object. Then we create a deformable mesh based on this 3D binary mask. The deformable model will be lead to the edge features in the volume with the help of image derived external forces. The deformable model segmentation result can be used to update the parameters for Gibbs Prior models. These methods will then work recursively to reach a global segmentation solution. The hybrid segmentation framework has been applied to images with the objective of lung, heart, colon, jaw, tumor, and brain. The experimental data includes MRI (T1, T2, PD), CT, X-ray, Ultra-Sound images. High quality results are achieved with relatively efficient time cost. We also did validation work using expert manual segmentation as the ground truth. The result shows that the hybrid segmentation may have further clinical use.

In computer vision and image analysis, image registration between 2D projections and a 3Dimage that achieves high accuracy and near real-time computation is challenging. In this paper, we propose a novel method that can rapidly detect an object’s 3D rigid motion or deformation from a 2D projection image or a small set thereof. The method is called CLARET (Correction via Limited-Angle Residues in External Beam Therapy) and consists of two stages: registration preceded by shape space and regression learning. In the registration stage, linear operators are used to iteratively estimate the motion/deformation parameters based on the current intensity residue between the target projec-tion(s) and the digitally reconstructed radiograph(s) (DRRs) of the estimated 3Dimage. The method determines the linear operators via a two-step learning process. First, it builds a low-order parametric model of the image region’s motion/deformation shape space from its prior 3Dimages. Second, using learning-time samples produced from the 3Dimages, it formulates the relationships between the model parameters and the co-varying 2D projection intensity residues by multi-scale linear regressions. The calculated multi-scale regression matrices yield the coarse-to-fine linear operators used in estimating the model parameters from the 2D projection intensity residues in the registration. The method’s application to Image-guided Radiation Therapy (IGRT) requires only a few seconds and yields good results in localizing a tumor under rigid motion in the head and neck and under respiratory deformation in the lung, using one treatment-time imaging 2D projection or a small set thereof. PMID:24058278

Terahertz (THz) wavelengths have attracted recent interest in multiple disciplines within engineering and science. Situated between the infrared and the microwave region of the electromagnetic spectrum, THz energy can propagate through non-polar materials such as clothing or packaging layers. Moreover, many chemical compounds, including explosives and many drugs, reveal strong absorption signatures in the THz range. For these reasons, THz wavelengths have great potential for non-destructive evaluation and explosive detection. Three-dimensional (3-D) reflection imaging with considerable depth resolution is also possible using pulsed THz systems. While THz imaging (especially 3-D) systems typically operate in transmission mode, reflection offers the most practical configuration for standoff detection, especially for objects with high water content (like human tissue) which are opaque at THz frequencies. In this research, reflection-based THz synthetic-aperture (SA) imaging is investigated as a potential imaging solution. THz SA imaging results presented in this dissertation are unique in that a 2-D planar synthetic array was used to generate a 3-Dimage without relying on a narrow time-window for depth isolation cite [Shen 2005]. Novel THz chemical detection techniques are developed and combined with broadband THz SA capabilities to provide concurrent 3-D spectral imaging. All algorithms are tested with various objects and pressed pellets using a pulsed THz time-domain system in the Northwest Electromagnetics and Acoustics Research Laboratory (NEAR-Lab).

The sagittal alignment of the pelvis can be evaluated by the angle of pelvic incidence (PI), which is constant for an arbitrary subject position and orientation and can be therefore compared among subjects in standing, sitting or supine position. In this study, PI was measured from three-dimensional (3D) computed tomography (CT) images of normal subjects that were acquired in supine position. A novel computerized method, based on image processing techniques, was developed to automatically determine the anatomical references required to measure PI, i.e. the centers of the femoral heads in 3D, and the center and inclination of the sacral endplate in 3D. Multiplanar image reformation was applied to obtain perfect sagittal views with all anatomical structures completely in line with the hip axis, from which PI was calculated. The resulting PI (mean+/-standard deviation) was equal to 46.6°+/-9.2° for male subjects (N = 189), 47.6°+/-10.7° for female subjects (N = 181), and 47.1°+/-10.0° for all subjects (N = 370). The obtained measurements of PI from 3Dimages were not biased by acquisition projection or structure orientation, because all anatomical structures were completely in line with the hip axis. The performed measurements in 3D therefore represent PI according to the actual geometrical relationships among anatomical structures of the sacrum, pelvis and hips, as observed from the perfect sagittal views.

The automated segmentation of the nucleus and cytoplasm regions in 3D optical CT microscope images has been achieved with two methods, a global threshold gradient based approach and a graph-cut approach. For the first method, the first two peaks of a gradient figure of merit curve are selected as the thresholds for cytoplasm and nucleus segmentation. The second method applies a graph-cut segmentation twice: the first identifies the nucleus region and the second identifies the cytoplasm region. Image segmentation of single cells is important for automated disease diagnostic systems. The segmentation methods were evaluated with 200 3Dimages consisting of 40 samples of 5 different cell types. The cell types consisted of columnar, macrophage, metaplastic and squamous human cells and cultured A549 cancer cells. The segmented cells were compared with both 2D and 3D reference images and the quality of segmentation was determined by the Dice Similarity Coefficient (DSC). In general, the graph-cut method had a superior performance to the gradient-based method. The graph-cut method achieved an average DSC of 86% and 72% for nucleus and cytoplasm segmentations respectively for the 2D reference images and 83% and 75% for the 3D reference images. The gradient method achieved an average DSC of 72% and 51% for nucleus and cytoplasm segmentation for the 2D reference images and 71% and 51% for the 3D reference images. The DSC of cytoplasm segmentation was significantly lower than for the nucleus since the cytoplasm was not differentiated as well by image intensity from the background.

We present a scheme of integrated optical 3-D digital imaging (IO3DI) based on digital signal processor (DSP), which can acquire range images independently without PC support. This scheme is based on a parallel hardware structure with aid of DSP and field programmable gate array (FPGA) to realize 3-Dimaging. In this integrated scheme of 3-Dimaging, the phase measurement profilometry is adopted. To realize the pipeline processing of the fringe projection, image acquisition and fringe pattern analysis, we present a multi-threads application program that is developed under the environment of DSP/BIOS RTOS (real-time operating system). Since RTOS provides a preemptive kernel and powerful configuration tool, with which we are able to achieve a real-time scheduling and synchronization. To accelerate automatic fringe analysis and phase unwrapping, we make use of the technique of software optimization. The proposed scheme can reach a performance of 39.5 f/s (frames per second), so it may well fit into real-time fringe-pattern analysis and can implement fast 3-Dimaging. Experiment results are also presented to show the validity of proposed scheme.

The nonuniform distributions of the residual stress were simulated by a 3D finite element model to analyze the elastic-plastic dynamic ultrasonic impact treatment (UIT) process of multiple impacts on the 2024 aluminum alloy. The evolution of the stress during the impact process was discussed. The successive impacts during the UIT process improve the uniformity of the plastic deformation and decrease the maximum compressive residual stress beneath the former impact indentations. The influences of different controlled parameters, including the initial impact velocity, pin diameter, pin tip, device moving, and offset distances, on the residual stress distributions were analyzed. The influences of the controlled parameters on the residual stress distributions are apparent in the offset direction due to the different surface coverage in different directions. The influences can be used to understand the UIT process and to obtain the desired residual stress by optimizing the controlled parameters.

This paper discusses the design and development of a miniature, high resolution 3-Dimaging sonar. The design utilizes frequency steered phased arrays (FSPA) technology. FSPAs present a small, low-power solution to the problem of underwater imaging sonars. The technology provides a method to build sonars with a large number of beams without the proportional power, circuitry and processing complexity. The design differs from previous methods in that the array elements are manufactured from a monolithic material. With this technique the arrays are flat and considerably smaller element dimensions are achievable which allows for higher frequency ranges and smaller array sizes. In the current frequency range, the demonstrated array has ultra high image resolution (1″ range×1° azimuth×1° elevation) and small size (<3″×3″). The design of the FSPA utilizes the phasing-induced frequency-dependent directionality of a linear phased array to produce multiple beams in a forward sector. The FSPA requires only two hardware channels per array and can be arranged in single and multiple array configurations that deliver wide sector 2-D images. 3-Dimages can be obtained by scanning the array in a direction perpendicular to the 2-D image field and applying suitable image processing to the multiple scanned 2-D images. This paper introduces the 3-D FSPA concept, theory and design methodology. Finally, results from a prototype array are presented and discussed. PMID:21112066

Reconstitute the 3-D model of the liver and its internal piping system and simulation of the liver surgical operation can increase the accurate and security of the liver surgical operation, attain a purpose for the biggest limit decrease surgical operation wound, shortening surgical operation time, increasing surgical operation succeeding rate, reducing medical treatment expenses and promoting patient recovering from illness. This text expatiated technology and method that the author constitutes 3-D the model of the liver and its internal piping system and simulation of the liver surgical operation according to the images of CT. The direct volume rendering method establishes 3D the model of the liver. Under the environment of OPENGL adopt method of space point rendering to display liver's internal piping system and simulation of the liver surgical operation. Finally, we adopt the wavelet transform method compressed the medical image data.

The original data is produced through standard magnetic resonance imaging (MRI) procedures with a surface coil applied to the lower back of a normal human subject. The 3-D spine image data consists of twenty-six contiguous slices with 256 x 256 pixels per slice. Two methods for visualization of the 3-D spine are explored. One method utilizes a verifocal mirror system which creates a true 3-D virtual picture of the object. Another method uses a standard high resolution monitor to simultaneously show the three orthogonal sections which intersect at any user-selected point within the object volume. We discuss the application of these systems in assessment of low back pain.

Reconstruction of three-dimensional (3D) scenes is an active research topic in the field of computer vision and 3D display. It's a challenge to model 3D objects rapidly and effectively. A 3D model can be extracted from multiple images. The system only requires a sequence of images taken with cameras without knowing the parameters of camera, which provide flexibility to a high degree. We focus on quickly merging point cloud of the object from depth map sequences. The whole system combines algorithms of different areas in computer vision, such as camera calibration, stereo correspondence, point cloud splicing and surface reconstruction. The procedure of 3D reconstruction is decomposed into a number of successive steps. Firstly, image sequences are received by the camera freely moving around the object. Secondly, the scene depth is obtained by a non-local stereo matching algorithm. The pairwise is realized with the Scale Invariant Feature Transform (SIFT) algorithm. An initial matching is then made for the first two images of the sequence. For the subsequent image that is processed with previous image, the point of interest corresponding to ones in previous images are refined or corrected. The vertical parallax between the images is eliminated. The next step is to calibrate camera, and intrinsic parameters and external parameters of the camera are calculated. Therefore, The relative position and orientation of camera are gotten. A sequence of depth maps are acquired by using a non-local cost aggregation method for stereo matching. Then point cloud sequence is achieved by the scene depths, which consists of point cloud model using the external parameters of camera and the point cloud sequence. The point cloud model is then approximated by a triangular wire-frame mesh to reduce geometric complexity and to tailor the model to the requirements of computer graphics visualization systems. Finally, the texture is mapped onto the wire-frame model, which can also be used for 3

Traditional techniques for visualizing anatomical structures are based on planar cross-sections from volume images, such as images obtained by computed tomography (CT) or magnetic resonance imaging (MRI). However, planar cross-sections taken in the coordinate system of the 3Dimage often do not provide sufficient or qualitative enough diagnostic information, because planar cross-sections cannot follow curved anatomical structures (e.g. arteries, colon, spine, etc). Therefore, not all of the important details can be shown simultaneously in any planar cross-section. To overcome this problem, reformatted images in the coordinate system of the inspected structure must be created. This operation is usually referred to as curved planar reformation (CPR). In this paper we propose an automated method for CPR of 3D spine images, which is based on the image transformation from the standard image-based to a novel spine-based coordinate system. The axes of the proposed spine-based coordinate system are determined on the curve that represents the vertebral column, and the rotation of the vertebrae around the spine curve, both of which are described by polynomial models. The optimal polynomial parameters are obtained in an image analysis based optimization framework. The proposed method was qualitatively and quantitatively evaluated on five CT spine images. The method performed well on both normal and pathological cases and was consistent with manually obtained ground truth data. The proposed spine-based CPR benefits from reduced structural complexity in favour of improved feature perception of the spine. The reformatted images are diagnostically valuable and enable easier navigation, manipulation and orientation in 3D space. Moreover, reformatted images may prove useful for segmentation and other image analysis tasks.

This article explains how a 3-D seismic data volume, a vertical seismic profile (VSP), electric well logs and reservoir pressure data can be used to image closely stacked thin-bed reservoirs. This interpretation focuses on the Oligocene Frio reservoir in South Texas which has multiple thin-beds spanning a vertical interval of about 3,000 ft.

Image registration is a powerful tool in various tomographic applications. Our main focus is on microCT applications in which samples/animals can be scanned multiple times under different conditions or at different time points. For this purpose, a registration tool capable of handling fairly large volumes has been developed, using a novel pseudo-3D method to achieve fast and interactive registration with simultaneous 3D visualization. To reduce computation complexity in 3D registration, we decompose it into several 2D registrations, which are applied to the orthogonal views (transaxial, sagittal and coronal) sequentially and iteratively. After registration in each view, the next view is retrieved with the new transformation matrix for registration. This reduces the computation complexity significantly. For rigid transform, we only need to search for 3 parameters (2 shifts, 1 rotation) in each of the 3 orthogonal views instead of 6 (3 shifts, 3 rotations) for full 3D volume. In addition, the amount of voxels involved is also significantly reduced. For the proposed pseudo-3D method, image-based registration is employed, with Sum of Square Difference (SSD) as the similarity measure. The searching engine is Powell's conjugate direction method. In this paper, only rigid transform is used. However, it can be extended to affine transform by adding scaling and possibly shearing to the transform model. We have noticed that more information can be used in the 2D registration if Maximum Intensity Projections (MIP) or Parallel Projections (PP) is used instead of the orthogonal views. Also, other similarity measures, such as covariance or mutual information, can be easily incorporated. The initial evaluation on microCT data shows very promising results. Two application examples are shown: dental samples before and after treatment and structural changes in materials before and after compression. Evaluation on registration accuracy between pseudo-3D method and true 3D method has

The U.S. Department of Defense Humanitarian Demining (HD) Research and Development Program focuses on developing, testing, demonstrating, and validating new technology for immediate use in humanitarian demining operations around the globe. Beginning in the late 1990's, the U.S. Army Countermine Division funded the development of the NIITEK ground penetrating radar (GPR) for detection of anti-tank (AT) landmines. This work is concerned with signal processing algorithms to suppress sources of artifacts in the NIITEK GPR, and formation of three-dimensional (3D) imagery from the resultant data. We first show that the NIITEK GPR data correspond to a 3D Synthetic Aperture Radar (SAR) database. An adaptive filtering method is utilized to suppress ground return and self-induced resonance (SIR) signals that are generated by the interaction of the radar-carrying platform and the transmitted radar signal. We examine signal processing methods to improve the fidelity of imagery for this 3D SAR system using pre-processing methods that suppress Doppler aliasing as well as other side lobe leakage artifacts that are introduced by the radar radiation pattern. The algorithm, known as digital spotlighting, imposes a filtering scheme on the azimuth-compressed SAR data, and manipulates the resultant spectral data to achieve a higher PRF to suppress the Doppler aliasing. We also present the 3D version of the Fourier-based wavefront reconstruction, a computationally-efficient and approximation-free SAR imaging method, for image formation with the NIITEK 3D SAR database.

The successful introduction of stereoscopic TV systems, such as Samsung's 3D Ready Plasma, requires high quality 3D content to be commercially available to the consumer. Console and PC games provide the most readily accessible source of high quality 3D content. This paper describes innovative developments in a generic, PC-based game driver architecture that addresses the two key issues affecting 3D gaming: quality and speed. At the heart of the quality issue are the same considerations that studios face producing stereoscopic renders from CG movies: how best to perform the mapping from a geometric CG environment into the stereoscopic display volume. The major difference being that for game drivers this mapping cannot be choreographed by hand but must be automatically calculated in real-time without significant impact on performance. Performance is a critical issue when dealing with gaming. Stereoscopic gaming has traditionally meant rendering the scene twice with the associated performance overhead. An alternative approach is to render the scene from one virtual camera position and use information from the z-buffer to generate a stereo pair using Depth-Image-Based Rendering (DIBR). We analyze this trade-off in more detail and provide some results relating to both 3Dimage quality and render performance.

Geophysical data are the main source of information about the subsurface. Geophysical techniques are, however, highly non-unique in determining specific physical parameters and boundaries of subsurface objects. To obtain actual physical information, an inversion process is often applied, in which measurements at or above the Earth surface are inverted into a 2- or 3-D subsurface spatial distribution of the physical property. Interpreting these models into structural objects, related to physical processes, requires a priori knowledge and expert analysis which is susceptible to subjective choices and is therefore often non-repeatable. In this research, we implemented a recently introduced object-based approach to interpret the 3-D inversion results of a single geophysical technique using the available a priori information and the physical and geometrical characteristics of the interpreted objects. The introduced methodology is semi-automatic and repeatable, and allows the extraction of subsurface structures using 3-D object-oriented image analysis (3-D OOA) in an objective knowledge-based classification scheme. The approach allows for a semi-objective setting of thresholds that can be tested and, if necessary, changed in a very fast and efficient way. These changes require only changing the thresholds used in a so-called ruleset, which is composed of algorithms that extract objects from a 3-D data cube. The approach is tested on a synthetic model, which is based on a priori knowledge on objects present in the study area (Tanzania). Object characteristics and thresholds were well defined in a 3-D histogram of velocity versus depth, and objects were fully retrieved. The real model results showed how 3-D OOA can deal with realistic 3-D subsurface conditions in which the boundaries become fuzzy, the object extensions become unclear and the model characteristics vary with depth due to the different physical conditions. As expected, the 3-D histogram of the real data was

Volume imaging in the pelvis has been well demonstrated to be an extremely useful technique, largely based on its ability to reconstruct the coronal plane of the uterus that usually cannot be visualized using traditional 2-dimensional (2D) imaging. As a result, this technique is now a part of the standard pelvic ultrasound protocol in many institutions. A variety of valuable applications of 3D sonography in the pelvis are discussed in this article. PMID:25444101

We develop a new formulation, mathematically elegant, to detect critical points of 3D scalar images. It is based on a topological number, which is the generalization to three dimensions of the 2D winding number. We illustrate our method by considering three different biomedical applications, namely, detection and counting of ovarian follicles and neuronal cells and estimation of cardiac motion from tagged MR images. Qualitative and quantitative evaluation emphasizes the reliability of the results. PMID:21317978

In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

Purpose: Transrectal ultrasound (TRUS) imaging is clinically used in prostate biopsy and therapy. Segmentation of the prostate on TRUS images has many applications. In this study, a three-dimensional (3D) segmentation method for TRUS images of the prostate is presented for 3D ultrasound-guided biopsy. Methods: This segmentation method utilizes a statistical shape, texture information, and intensity profiles. A set of wavelet support vector machines (W-SVMs) is applied to the images at various subregions of the prostate. The W-SVMs are trained to adaptively capture the features of the ultrasound images in order to differentiate the prostate and nonprostate tissue. This method consists of a set of wavelet transforms for extraction of prostate texture features and a kernel-based support vector machine to classify the textures. The voxels around the surface of the prostate are labeled in sagittal, coronal, and transverse planes. The weight functions are defined for each labeled voxel on each plane and on the model at each region. In the 3D segmentation procedure, the intensity profiles around the boundary between the tentatively labeled prostate and nonprostate tissue are compared to the prostate model. Consequently, the surfaces are modified based on the model intensity profiles. The segmented prostate is updated and compared to the shape model. These two steps are repeated until they converge. Manual segmentation of the prostate serves as the gold standard and a variety of methods are used to evaluate the performance of the segmentation method. Results: The results from 40 TRUS image volumes of 20 patients show that the Dice overlap ratio is 90.3% ± 2.3% and that the sensitivity is 87.7% ± 4.9%. Conclusions: The proposed method provides a useful tool in our 3D ultrasound image-guided prostate biopsy and can also be applied to other applications in the prostate. PMID:22755682

Three dimensions (3D) acquisition systems are driving applications in many research field. Nowadays 3D acquiring systems are used in a lot of applications, such as cinema industry or in automotive (for active security systems). Depending on the application, systems present different features, for example color sensitivity, bi-dimensional image resolution, distance measurement accuracy and acquisition frame rate. The system we developed acquires 3D movie using indirect Time of Flight (iTOF), starting from phase delay measurement of a sinusoidally modulated light. The system acquires live movie with a frame rate up to 50frame/s in a range distance between 10 cm up to 7.5 m.

A fully automatic novel algorithm is presented for accurate 3-D segmentation of the human sternum in lung multi detector computed tomography (MDCT) images. The segmentation result is refined by employing active contours to remove calcified costal cartilage that is attached to the sternum. For each dataset, costal notches (sternocostal joints) are localized in 3-D by using a sternum mask and positions of the costal notches on it as reference. The proposed algorithm for sternum segmentation was tested on 16 complete lung MDCT datasets and comparison of the segmentation results to the reference delineation provided by a radiologist, shows high sensitivity (92.49%) and specificity (99.51%) and small mean distance (dmean=1.07 mm). Total average of the Euclidean distance error for costal notches positioning in 3-D is 4.2 mm. PMID:24110446

In this paper, we present approaches toward an interactive visualization of a real time input, applied to 3-D visualizations of 2-D ultrasound echography data. The first, 3 degrees-of- freedom (DOF) incremental system visualizes a 3-D volume acquired as a stream of 2-D slices with location and orientation with 3 DOF. As each slice arrives, the system reconstructs a regular 3-D volume and renders it. Rendering is done by an incremental image-order ray- casting algorithm which stores and reuses the results of expensive resampling along the rays for speed. The second is our first experiment toward real-time 6 DOF acquisition and visualization. Two-dimensional slices with 6 DOF are reconstructed off-line, and visualized at an interactive rate using a parallel volume rendering code running on the graphics multicomputer Pixel-Planes 5.

So far, works on ultrasonic diffraction imaging are based on scalar theory of sound wave. This is not correct as sound has vector nature. But when sound propagates in solids, its vector nature has to be considered as polarization occurs and transverse wave as well as longitudinal wave will appear. Vector theory is especially needed when the obstacle size is smaller than the wavelength. We use the Smythe-Kirchhoff approach for the vector theory of diffraction. We derive the image formation theory based on the vector diffraction theory. The effect of polarization on acoustical imaging is discussed.

In this paper, we propose to use 2D image projections to automatically segment a needle in a 3D ultrasound image. This approach is motivated by the twin observations that the needle is more conspicuous in a projected image, and its projected area is a minimum when the rays are cast parallel to the needle direction. To avoid the computational burden of an exhaustive 2D search for the needle direction, a faster 1D search procedure is proposed. First, a plane which contains the needle direction is determined by the initial projection direction and the (estimated) direction of the needle in the corresponding projection image. Subsequently, an adaptive 1D search technique is used to adjust the projection direction iteratively until the projected needle area is minimized. In order to remove noise and complex background structure from the projection images, a priori information about the needle position and orientation is used to crop the 3D volume, and the cropped volume is rendered with Gaussian transfer functions. We have evaluated this approach experimentally using agar and turkey breast phantoms. The results show that it can find the 3D needle orientation within 1 degree, in about 1 to 3 seconds on a 500 MHz computer.

The paper presents the project which was carried out in the Photogrammetric Laboratory of Warsaw University of Technology. The experiment is concerned with the extraction of 3D vector data for buildings creation from 3D photogrammetric model based on the Ikonos stereo images. The model was reconstructed with photogrammetric workstation - Summit Evolution combined with ArcGIS 3D platform. Accuracy of 3D model was significantly improved by use for orientation of pair of satellite images the stereo measured tie points distributed uniformly around the model area in addition to 5 control points. The RMS for model reconstructed on base of the RPC coefficients only were 16,6 m, 2,7 m and 47,4 m, for X, Y and Z coordinates, respectively. By addition of 5 control points the RMS were improved to 0,7 m, 0,7 m 1,0 m, where the best results were achieved when RMS were estimated from deviations in 17 check points (with 5 control points)and amounted to 0,4 m, 0,5 m and 0,6 m, for X, Y, and Z respectively. The extracted 3D vector data for buildings were integrated with 2D data of the ground footprints and afterwards they were used for 3D modelling of buildings in Google SketchUp software. The final results were compared with the reference data obtained from other sources. It was found that the shape of buildings (in concern to the number of details) had been reconstructed on level of LoD1, when the accuracy of these models corresponded to the level of LoD2.

This article tackles the problem of estimating non-rigid human 3D shape and motion from image sequences taken by uncalibrated cameras. Similar to other state-of-the-art solutions we factorize 2D observations in camera parameters, base poses and mixing coefficients. Existing methods require sufficient camera motion during the sequence to achieve a correct 3D reconstruction. To obtain convincing 3D reconstructions from arbitrary camera motion, our method is based on a-priorly trained base poses. We show that strong periodic assumptions on the coefficients can be used to define an efficient and accurate algorithm for estimating periodic motion such as walking patterns. For the extension to non-periodic motion we propose a novel regularization term based on temporal bone length constancy. In contrast to other works, the proposed method does not use a predefined skeleton or anthropometric constraints and can handle arbitrary camera motion. We achieve convincing 3D reconstructions, even under the influence of noise and occlusions. Multiple experiments based on a 3D error metric demonstrate the stability of the proposed method. Compared to other state-of-the-art methods our algorithm shows a significant improvement. PMID:27093439

Imaging systems in millimeter waves are required for applications in medicine, communications, homeland security, and space technology. This is because there is no known ionization hazard for biological tissue, and atmospheric attenuation in this range of the spectrum is low compared to that of infrared and optical rays. The lack of an inexpensive room temperature detector makes it difficult to give a suitable real time implement for the above applications. A 3D MMW imaging system based on chirp radar was studied previously using a scanning imaging system of a single detector. The system presented here proposes to employ a chirp radar method with Glow Discharge Detector (GDD) Focal Plane Array (FPA of plasma based detectors) using heterodyne detection. The intensity at each pixel in the GDD FPA yields the usual 2D image. The value of the I-F frequency yields the range information at each pixel. This will enable 3D MMW imaging. In this work we experimentally demonstrate the feasibility of implementing an imaging system based on radar principles and FPA of inexpensive detectors. This imaging system is shown to be capable of imaging objects from distances of at least 10 meters.

Modelling of 3D objects from image sequences is a challenging problem and has been an important research topic in the areas of photogrammetry and computer vision for many years. In this paper, a system is presented which automatically extracts a textured 3D surface model from a sequence of images of a scene. The system can deal with unknown camera settings. In addition, the parameters of this camera are allowed to change during acquisition (e.g., by zooming or focusing). No prior knowledge about the scene is necessary to build the 3D models. Therefore, this system offers a high degree of flexibility. The system is based on state-of-the-art algorithms recently developed in computer vision. The 3D modelling task is decomposed into a number of successive steps. Gradually, more knowledge of the scene and the camera setup is retrieved. At this point, the obtained accuracy is not yet at the level required for most metrology applications, but the visual quality is very convincing. This system has been applied to a number of applications in archaeology. The Roman site of Sagalassos (southwest Turkey) was used as a test case to illustrate the potential of this new approach.

A synchrotron radiation computed microtomography system allowing high resolution 3Dimaging of bone samples has been developed at ESRF. The system uses a high resolution 2D detector based on a CCd camera coupled to a fluorescent screen through light optics. The spatial resolution of the device is particularly well adapted to the imaging of bone structure. In view of studying growth, vertebra samples of fetus with differential gestational ages were imaged. The first results show that fetus vertebra is quite different from adult bone both in terms of density and organization.

In this paper, a method for constructing photorealistic textured model using 3D structured light digitizer is presented. Our method acquisition of range images and texture images around object, and range images are registered and integrated to construct geometric model of object. System is calibrated and poses of texture-camera are determined so that the relationship between texture and geometric model is established. After that, a global optimization is applied to assign compatible texture to adjacent surface and followed with a level procedure to remove artifacts due to vary lighting, approximate geometric model and so on. Lastly, we demonstrate the effect of our method on constructing a real model of world.

The most frequent reasons for revision of total knee arthroplasty are loosening and abnormal axial alignment leading to an unphysiological kinematic of the knee implant. To get an idea about the postoperative kinematic of the implant, it is essential to determine the position and orientation of the tibial and femoral prosthesis. Therefore we developed a registration method for fitting 3D CAD-models of knee joint prostheses into an 3D MR image. This rigid registration is the basis for a quantitative analysis of the kinematics of knee implants. Firstly the surface data of the prostheses models are converted into a voxel representation; a recursive algorithm determines all boundary voxels of the original triangular surface data. Secondly an initial preconfiguration of the implants by the user is still necessary for the following step: The user has to perform a rough preconfiguration of both remaining prostheses models, so that the fine matching process gets a reasonable starting point. After that an automated gradient-based fine matching process determines the best absolute position and orientation: This iterative process changes all 6 parameters (3 rotational- and 3 translational parameters) of a model by a minimal amount until a maximum value of the matching function is reached. To examine the spread of the final solutions of the registration, the interobserver variability was measured in a group of testers. This variability, calculated by the relative standard deviation, improved from about 50% (pure manual registration) to 0.5% (rough manual preconfiguration and subsequent fine registration with the automatic fine matching process).

Recent developments in 3Dimaging lidar are presented. Long range 3Dimaging using photon counting is now a possibility, offering a low-cost approach to integrated remote sensing with step changing advantages in size, weight and power compared to conventional analogue active imaging technology. We report results using a Geiger-mode array for time-of-flight, single photon counting lidar for depth profiling and determination of the shape and size of tree canopies and distributed surface reflections at a range of 9km, with 4μJ pulses with a frame rate of 100kHz using a low-cost fibre laser operating at a wavelength of λ=1.5 μm. The range resolution is less than 4cm providing very high depth resolution for target identification. This specification opens up several additional functionalities for advanced lidar, for example: absolute rangefinding and depth profiling for long range identification, optical communications, turbulence sensing and time-of-flight spectroscopy. Future concepts for 3D time-of-flight polarimetric and multispectral imaging lidar, with optical communications in a single integrated system are also proposed.

Linearized methods are presented for appraising image resolution and parameter accuracy in images generated with two and three dimensional non-linear electromagnetic inversion schemes. When direct matrix inversion is employed, the model resolution and posterior model covariance matrices can be directly calculated. A method to examine how the horizontal and vertical resolution varies spatially within the electromagnetic property image is developed by examining the columns of the model resolution matrix. Plotting the square root of the diagonal of the model covariance matrix yields an estimate of how errors in the inversion process such as data noise and incorrect a priori assumptions about the imaged model map into parameter error. This type of image is shown to be useful in analyzing spatial variations in the image sensitivity to the data. A method is analyzed for statistically estimating the model covariance matrix when the conjugate gradient method is employed rather than a direct inversion technique (for example in 3D inversion). A method for calculating individual columns of the model resolution matrix using the conjugate gradient method is also developed. Examples of the image analysis techniques are provided on 2D and 3D synthetic cross well EM data sets, as well as a field data set collected at the Lost Hills Oil Field in Central California.

A male metal worker, who has never smoked, contracted debilitating dyspnoea in 2003 which then deteriorated until 2007. Spirometry and chest x-rays provided no diagnosis. A 3D-image of the airways was reconstructed from a high-resolution CT (HRCT) in 2007, showing peribronchial air on the right side, mostly along the presegmental airways. After digital subtraction of the image of the peribronchial air, a hole on the cranial side of the right main bronchus was detected. The perforation could be identified at the re-examination of HRCTs in 2007 and 2009, but not in 2010 when it had possibly healed. The occupational exposure of the patient to evaporating chemicals might have contributed to the perforation and hampered its healing. A 3D HRCT reconstruction should be considered to detect bronchial anomalies, including wall-perforation, when unexplained dyspnoea or other chest symptoms call for extended investigation. PMID:22679238

Fluorescence nanoscopy, or super-resolution microscopy, has become an important tool in cell biological research. However, because of its usually inferior resolution in the depth direction (50-80 nm) and rapidly deteriorating resolution in thick samples, its practical biological application has been effectively limited to two dimensions and thin samples. Here, we present the development of whole-cell 4Pi single-molecule switching nanoscopy (W-4PiSMSN), an optical nanoscope that allows imaging of three-dimensional (3D) structures at 10- to 20-nm resolution throughout entire mammalian cells. We demonstrate the wide applicability of W-4PiSMSN across diverse research fields by imaging complex molecular architectures ranging from bacteriophages to nuclear pores, cilia, and synaptonemal complexes in large 3D cellular volumes. PMID:27397506

It is a big challenge capturing and modeling 3D information of the built environment. A number of techniques and technologies are now in use. These include GPS, and photogrammetric application and also remote sensing applications. The experiment uses multi-source data fusion technology for 3D scene reconstruction based on the principle of 3D laser scanning technology, which uses the laser point cloud data as the basis and Digital Ortho-photo Map as an auxiliary, uses 3DsMAX software as a basic tool for building three-dimensional scene reconstruction. The article includes data acquisition, data preprocessing, 3D scene construction. The results show that the 3D scene has better truthfulness, and the accuracy of the scene meet the need of 3D scene construction.

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3Dimages can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

Seismic imaging challenges in the Deepwater GOM include surface and sediment related multiples and issues arising from complicated salt bodies. Frequently, wells encounter geologic complexity not resolved on conventional surface seismic section. To help address these challenges BP has been acquiring 3D VSP (Vertical Seismic Profile) surveys in the Deepwater GOM. The procedure involves placing an array of seismic sensors in the borehole and acquiring a 3D seismic dataset with a surface seismic gunboat that fires airguns in a spiral pattern around the wellbore. Placing the seismic geophones in the borehole provides a higher resolution and more accurate image near the borehole, as well as other advantages relating to the unique position of the sensors relative to complex structures. Technical objectives are to complement surface seismic with improved resolution (~2X seismic), better high dip structure definition (e.g. salt flanks) and to fill in "imaging holes" in complex sub-salt plays where surface seismic is blind. Business drivers for this effort are to reduce risk in well placement, improved reserve calculation and understanding compartmentalization and stratigraphic variation. To date, BP has acquired 3D VSP surveys in ten wells in the DW GOM. The initial results are encouraging and show both improved resolution and structural images in complex sub-salt plays where the surface seismic is blind. In conjunction with this effort BP has influenced both contractor borehole seismic tool design and developed methods to enable the 3D VSP surveys to be conducted offline thereby avoiding the high daily rig costs associated with a Deepwater drilling rig.

Understanding the deformation of the tongue during human speech is important for head and neck surgeons and speech and language scientists. Tagged magnetic resonance (MR) imaging can be used to image 2D motion, and data from multiple image planes can be combined via post-processing to yield estimates of 3D motion. However, lacking boundary information, this approach suffers from inaccurate estimates near the tongue surface. This paper describes a method that combines two sources of information to yield improved estimation of 3D tongue motion. The method uses the harmonic phase (HARP) algorithm to extract motion from tags and diffeomorphic demons to provide surface deformation. It then uses an incompressible deformation estimation algorithm to incorporate both sources of displacement information to form an estimate of the 3D whole tongue motion. Experimental results show that use of combined information improves motion estimation near the tongue surface, a problem that has previously been reported as problematic in HARP analysis, while preserving accurate internal motion estimates. Results on both normal and abnormal tongue motions are shown. PMID:24505742

Discretization by rasterization is introduced into the method of images (MI) in the context of 3D deterministic radio propagation modeling as a way to exploit spatial coherence of electromagnetic propagation for fine-grained parallelism. Traditional algebraic treatment of bounding regions and surfaces is replaced by computer graphics rendering of 3D reflections and double refractions while building the image tree. The visibility of reception points and surfaces is also resolved by shader programs. The proposed rasterization is shown to be of comparable run time to that of the fundamentally parallel shooting and bouncing rays. The rasterization does not affect the signal evaluation backtracking step, thus preserving its advantage over the brute force ray-tracing methods in terms of accuracy. Moreover, the rendering resolution may be scaled back for a given level of scenario detail with only marginal impact on the image tree size. This allows selection of scene optimized execution parameters for faster execution, giving the method a competitive edge. The proposed variant of MI can be run on any GPU that supports real-time 3D graphics.

INSAT-3D is an advanced meteorological satellite of ISRO which acquires imagery in optical and infra-red (IR) channels for study of weather dynamics in Indian sub-continent region. In this paper, methodology of radiometric quality evaluation for Level-1 products of Imager, one of the payloads onboard INSAT-3D, is described. Firstly, overall visual quality of scene in terms of dynamic range, edge sharpness or modulation transfer function (MTF), presence of striping and other image artefacts is computed. Uniform targets in Desert and Sea region are identified for which detailed radiometric performance evaluation for IR channels is carried out. Mean brightness temperature (BT) of targets is computed and validated with independently generated radiometric references. Further, diurnal/seasonal trends in target BT values and radiometric uncertainty or sensor noise are studied. Results of radiometric quality evaluation over duration of eight months (January to August 2014) and comparison of radiometric consistency pre/post yaw flip of satellite are presented. Radiometric Analysis indicates that INSAT-3Dimages have high contrast (MTF > 0.2) and low striping effects. A bias of <4K is observed in the brightness temperature values of TIR-1 channel measured during January-August 2014 indicating consistent radiometric calibration. Diurnal and seasonal analysis shows that Noise equivalent differential temperature (NEdT) for IR channels is consistent and well within specifications.

Breast reconstruction is an important part of the breast cancer treatment process for many women. Recently, 2D and 3Dimages have been used by plastic surgeons for evaluating surgical outcomes. Distances between different fiducial points are frequently used as quantitative measures for characterizing breast morphology. Fiducial points can be directly marked on subjects for direct anthropometry, or can be manually marked on images. This paper introduces novel algorithms to automate the identification of fiducial points in 3Dimages. Automating the process will make measurements of breast morphology more reliable, reducing the inter- and intra-observer bias. Algorithms to identify three fiducial points, the nipples, sternal notch, and umbilicus, are described. The algorithms used for localization of these fiducial points are formulated using a combination of surface curvature and 2D color information. Comparison of the 3D co-ordinates of automatically detected fiducial points and those identified manually, and geodesic distances between the fiducial points are used to validate algorithm performance. The algorithms reliably identified the location of all three of the fiducial points. We dedicate this article to our late colleague and friend, Dr. Elisabeth K. Beahm. Elisabeth was both a talented plastic surgeon and physician-scientist; we deeply miss her insight and her fellowship. PMID:25288903

Fluid registration is widely used in medical imaging to track anatomical changes, to correct image distortions, and to integrate multi-modality data. Fluid mappings guarantee that the template image deforms smoothly into the target, without tearing or folding, even when large deformations are required for accurate matching. Here we implemented an intensity-based fluid registration algorithm, accelerated by using a filter designed by Bro-Nielsen and Gramkow. We validated the algorithm on 2D and 3D geometric phantoms using the mean square difference between the final registered image and target as a measure of the accuracy of the registration. In tests on phantom images with different levels of overlap, varying amounts of Gaussian noise, and different intensity gradients, the fluid method outperformed a more commonly used elastic registration method, both in terms of accuracy and in avoiding topological errors during deformation. We also studied the effect of varying the viscosity coefficients in the viscous fluid equation, to optimize registration accuracy. Finally, we applied the fluid registration algorithm to a dataset of 2D binary corpus callosum images and 3D volumetric brain MRIs from 14 healthy individuals to assess its accuracy and robustness.

Femoroacetabular impingement is uncommonly associated with a large rim fragment of bone along the superolateral acetabulum. We report an unusual case of femoroacetabular impingement (FAI) with chronic acetabular rim fracture. Radiographic, 3D computed tomography, 3D magnetic resonance imaging and arthroscopy correlation is presented with discussion of relative advantages and disadvantages of various modalities in the context of FAI. PMID:26191497

Stereotactic X-ray mammography (SM) and ultrasound (US) guidance are both commonly used for breast biopsy. While SM provides three-dimensional (3D) targeting information and US provides real-time guidance, both have limitations. SM is a long and uncomfortable procedure and the US guided procedure is inherently two dimensional (2D), requiring a skilled physician for both safety and accuracy. The authors developed a 3D US-guided biopsy system to be integrated with, and to supplement SM imaging. Their goal is to be able to biopsy a larger percentage of suspicious masses using US, by clarifying ambiguous structures with SM imaging. Features from SM and US guided biopsy were combined, including breast stabilization, a confined needle trajectory, and dual modality imaging. The 3D US guided biopsy system uses a 7.5 MHz breast probe and is mounted on an upright SM machine for preprocedural imaging. Intraprocedural targeting and guidance was achieved with real-time 2D and near real-time 3D US imaging. Postbiopsy 3D US imaging allowed for confirmation that the needle was penetrating the target. The authors evaluated 3D US-guided biopsy accuracy of their system using test phantoms. To use mammographic imaging information, they registered the SM and 3D US coordinate systems. The 3D positions of targets identified in the SM images were determined with a target localization error (TLE) of 0.49 mm. The z component (x-ray tube to image) of the TLE dominated with a TLE{sub z} of 0.47 mm. The SM system was then registered to 3D US, with a fiducial registration error (FRE) and target registration error (TRE) of 0.82 and 0.92 mm, respectively. Analysis of the FRE and TRE components showed that these errors were dominated by inaccuracies in the z component with a FRE{sub z} of 0.76 mm and a TRE{sub z} of 0.85 mm. A stereotactic mammography and 3D US guided breast biopsy system should include breast compression for stability and safety and dual modality imaging for target localization

Pavement condition surveying is vital for pavement maintenance programs that ensure ride quality and traffic safety. This paper first introduces an automated pavement inspection system which uses a three-dimensional (3D) camera and a structured laser light to acquire dense transverse profiles of a pavement lane surface when it carries a moving vehicle. After the calibration, the 3D system can yield a depth resolution of 0.5 mm and a transverse resolution of 1.56 mm pixel-1 at 1.4 m camera height from the ground. The scanning rate of the camera can be set to its maximum at 5000 lines s-1, allowing the density of scanned profiles to vary with the vehicle's speed. The paper then illustrates the algorithms that utilize 3D information to detect pavement distress, such as transverse, longitudinal and alligator cracking, and presents the field tests on the system's repeatability when scanning a sample pavement in multiple runs at the same vehicle speed, at different vehicle speeds and under different weather conditions. The results show that this dedicated 3D system can capture accurate pavement images that detail surface distress, and obtain consistent crack measurements in repeated tests and under different driving and lighting conditions.

Laser imaging has recently been identified as a potential tool for rock mass characterization. This contribution focuses on the application of triangulation based, short-range laser imaging to determine fracture orientation and surface texture. This technology measures the distance to the target by triangulating the projected and reflected laser beams, and also records the reflection intensity. In this study, we acquired 3D laser images of rock faces using the Laser Camera System (LCS), a portable instrument developed by Neptec Design Group (Ottawa, Canada). The LCS uses an infrared laser beam and is immune to the lighting conditions. The maximum image resolution is 1024 x 1024 volumetric image elements. Depth resolution is 0.5 mm at 5 m. An above ground field trial was conducted at a blocky road cut with well defined joint sets (Kingston, Ontario). An underground field trial was conducted at the Inco 175 Ore body (Sudbury, Ontario) where images were acquired in the dark and the joint set features were more subtle. At each site, from a distance of 3 m away from the rock face, a grid of six images (approximately 1.6 m by 1.6 m) was acquired at maximum resolution with 20% overlap between adjacent images. This corresponds to a density of 40 image elements per square centimeter. Polyworks, a high density 3D visualization software tool, was used to align and merge the images into a single digital triangular mesh. The conventional method of determining fracture orientations is by manual measurement using a compass. In order to be accepted as a substitute for this method, the LCS should be capable of performing at least to the capabilities of manual measurements. To compare fracture orientation estimates derived from the 3D laser images to manual measurements, 160 inclinometer readings were taken at the above ground site. Three prominent joint sets (strike/dip: 236/09, 321/89, 325/01) were identified by plotting the joint poles on a stereonet. Underground, two main joint

We describe a device which has the potential to be used both as a virtual image display and as a backlight. The pupil of the emitted light fills the device approximately to its periphery and the collimated emission can be scanned both horizontally and vertically in the manner needed to illuminate an eye in any position. The aim is to reduce the power needed to illuminate a liquid crystal panel but also to enable a smooth transition from 3D to a virtual image as the user nears the screen. PMID:23938645

Pore geometry imaging and its quantitative description is a key factor for advances in the knowledge of physical, chemical and biological soil processes. For many years photos from flattened surfaces of undisturbed soil samples impregnated with fluorescent resin and from soil thin sections under microscope have been the only way available for exploring pore architecture at different scales. Earlier 3D representations of the internal structure of the soil based on not destructive methods have been obtained using medical tomographic systems (NMR and X-ray CT). However, images provided using such equipments, show strong limitations in terms of spatial resolution. In the last decade very good results have then been obtained using imaging from very expensive systems based on synchrotron radiation. More recently, X-ray Micro-Tomography has resulted the most widely applied being the technique showing the best compromise between costs, resolution and size of the images. Conversely, the conceptually simpler but destructive method of "serial sectioning" has been progressively neglected for technical problems in sample preparation and time consumption needed to obtain an adequate number of serial sections for correct 3D reconstruction of soil pore geometry. In this work a comparison between the two methods above has been carried out in order to define advantages, shortcomings and to point out their different potential. A cylindrical undisturbed soil sample 6.5cm in diameter and 6.5cm height of an Ap horizon of an alluvial soil showing vertic characteristics, has been reconstructed using both a desktop X-ray micro-tomograph Skyscan 1172 and the new automatic serial sectioning system SSAT (Sequential Section Automatic Tomography) set up at CNR ISAFOM in Ercolano (Italy) with the aim to overcome most of the typical limitations of such a technique. Image best resolution of 7.5 µm per voxel resulted using X-ray Micro CT while 20 µm was the best value using the serial sectioning

A new image matching technique is described. It is implemented as an object-independent hierarchical structural juxtaposition algorithm based on an alphabet of simple object-independent contour structural elements. The structural matching applied implements an optimized method of walking through a truncated tree of all possible juxtapositions of two sets of structural elements. The algorithm was initially developed for dealing with 2D images such as the aerospace photographs, and it turned out to be sufficiently robust and reliable for matching successfully the pictures of natural landscapes taken in differing seasons from differing aspect angles by differing sensors (the visible optical, IR, and SAR pictures, as well as the depth maps and geographical vector-type maps). At present (in the reported version), the algorithm is enhanced based on additional use of information on third spatial coordinates of observed points of object surfaces. Thus, it is now capable of matching the images of 3D scenes in the tasks of automatic navigation of extremely low flying unmanned vehicles or autonomous terrestrial robots. The basic principles of 3D structural description and matching of images are described, and the examples of image matching are presented.

The problem of generating realistic computer models of objects represented by 3D segmented images is important in many biomedical applications. Labelled 3Dimages impose particular challenges for meshing algorithms because multi-material junctions form features such as surface pacthes, edges and corners which need to be preserved into the output mesh. In this paper, we propose a feature preserving Delaunay refinement algorithm which can be used to generate high-quality tetrahedral meshes from segmented images. The idea is to explicitly sample corners and edges from the input image and to constrain the Delaunay refinement algorithm to preserve these features in addition to the surface patches. Our experimental results on segmented medical images have shown that, within a few seconds, the algorithm outputs a tetrahedral mesh in which each material is represented as a consistent submesh without gaps and overlaps. The optimization property of the Delaunay triangulation makes these meshes suitable for the purpose of realistic visualization or finite element simulations. PMID:20426123

This paper examines the results of image enhancement and point cloud filtering on the visual and geometric quality of 3D models for the representation of underwater features. Specifically it evaluates the combination of effects from the manual editing of images' radiometry (captured at shallow depths) and the selection of parameters for point cloud definition and mesh building (processed in 3D modeling software). Such datasets, are usually collected by divers, handled by scientists and used for geovisualization purposes. In the presented study, have been created 3D models from three sets of images (seafloor, part of a wreck and a small boat's wreck) captured at three different depths (3.5m, 10m and 14m respectively). Four models have been created from the first dataset (seafloor) in order to evaluate the results from the application of image enhancement techniques and point cloud filtering. The main process for this preliminary study included a) the definition of parameters for the point cloud filtering and the creation of a reference model, b) the radiometric editing of images, followed by the creation of three improved models and c) the assessment of results by comparing the visual and the geometric quality of improved models versus the reference one. Finally, the selected technique is tested on two other data sets in order to examine its appropriateness for different depths (at 10m and 14m) and different objects (part of a wreck and a small boat's wreck) in the context of an ongoing research in the Laboratory of Photogrammetry and Remote Sensing.

Mesoscale phenomena in magnetism will add essential parameters to improve speed, size and energy efficiency of spin driven devices. Multidimensional visualization techniques will be crucial to achieve mesoscience goals. Magnetic tomography is of large interest to understand e.g. interfaces in magnetic multilayers, the inner structure of magnetic nanocrystals, nanowires or the functionality of artificial 3D magnetic nanostructures. We have developed tomographic capabilities with magnetic full-field soft X-ray microscopy combining X-MCD as element specific magnetic contrast mechanism, high spatial and temporal resolution due to the Fresnel zone plate optics. At beamline 6.1.2 at the ALS (Berkeley CA) a new rotation stage allows recording an angular series (up to 360 deg) of high precision 2D projection images. Applying state-of-the-art reconstruction algorithms it is possible to retrieve the full 3D structure. We will present results on prototypic rolled-up Ni and Co/Pt tubes and glass capillaries coated with magnetic films and compare to other 3Dimaging approaches e.g. in electron microscopy. Supported by BES MSD DOE Contract No. DE-AC02-05-CH11231 and ERC under the EU FP7 program (grant agreement No. 306277).

A computer vision approach for the extraction of feature points on 3Dimages of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3Dimages of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

Performance of denoising based on discrete cosine transform applied to multichannel remote sensing images corrupted by additive white Gaussian noise is analyzed. Images obtained by satellite Earth Observing-1 (EO-1) mission using hyperspectral imager instrument (Hyperion) that have high input SNR are taken as test images. Denoising performance is characterized by improvement of PSNR. For hard-thresholding 3D DCT-based denoising, simple statistics (probabilities to be less than a certain threshold) are used to predict denoising efficiency using curves fitted into scatterplots. It is shown that the obtained curves (approximations) provide prediction of denoising efficiency with high accuracy. Analysis is carried out for different numbers of channels processed jointly. Universality of prediction for different number of channels is proven.

Generating accurate three dimensional planetary models is becoming increasingly important as NASA plans manned missions to return to the Moon in the next decade. This paper describes a 3D surface reconstruction system called the Ames Stereo Pipeline that is designed to produce such models automatically by processing orbital stereo imagery. We discuss two important core aspects of this system: (1) refinement of satellite station positions and pose estimates through least squares bundle adjustment; and (2) a stochastic plane fitting algorithm that generalizes the Lucas-Kanade method for optimal matching between stereo pair images.. These techniques allow us to automatically produce seamless, highly accurate digital elevation models from multiple stereo image pairs while significantly reducing the influence of image noise. Our technique is demonstrated on a set of 71 high resolution scanned images from the Apollo 15 mission

A 3D solid model-aided object cueing method that matches phase angles of directional derivative vectors at image pixels to phase angles of vectors normal to projected model edges is described. It is intended for finding specific types of objects at arbitrary position and orientation in overhead images, independent of spatial resolution, obliqueness, acquisition conditions, and type of imaging sensor. It is shown that the phase similarity measure can be efficiently evaluated over all combinations of model position and orientation using the FFT. The highest degree of similarity over all model orientations is captured in a match surface of similarity values vs. model position. Unambiguous peaks in this surface are sorted in descending order of similarity value, and the small image thumbnails that contain them are presented to human analysts for inspection in sorted order.

Reconstructing 3D structure of scenes in the scattering medium is a challenging task with great research value. Existing techniques often impose strong assumptions on the scattering behaviors and are of limited performance. Recently, a low-cost transient imaging system has provided a feasible way to resolve the scene depth, by detecting the reflection instant on the time profile of a surface point. However, in cases with scattering medium, the rays are both reflected and scattered during transmission, and the depth calculated from the time profile largely deviates from the true value. To handle this problem, we used the different polarization behaviors of the reflection and scattering components, and introduced active polarization to separate the reflection component to estimate the scattering robust depth. Our experiments have demonstrated that our approach can accurately reconstruct the 3D structure underlying the scattering medium. PMID:27607944

Telerobotics studies remote control of distant robots by a human operator using supervisory or direct control. Even if the robot manipulators has vision or other senses, problems arise involving control, communications, and delay. The communication delays that may be expected with telerobots working in space stations while being controlled from an Earth lab have led to a number of experiments attempting to circumvent the problem. This delay in communication is a main motivating factor in moving from well understood instantaneous hands-on manual control to less well understood supervisory control; the ultimate step would be the realization of a fully autonomous robot. The 3-D model control plays a crucial role in resolving many conflicting image processing problems that are inherent in resolving in the bottom-up approach of most current machine vision processes. The 3-D model control approach is also capable of providing the necessary visual feedback information for both the control algorithms and for the human operator.

This paper addresses the problem of 3D surface scan refinement, which is desirable due to noise, outliers, and missing measurements being present in the 3D surfaces obtained with a laser scanner. We present a novel algorithm for the fusion of absolute laser scanner depth profiles and photometrically estimated surface normal data, which yields a noise-reduced and highly detailed depth profile with large scale shape robustness. In contrast to other approaches published in the literature, the presented algorithm (1) regards non-Lambertian surfaces, (2) simultaneously computes surface reflectance (i.e. BRDF) parameters required for 3D reconstruction, (3) models pixelwise incident light and viewing directions, and (4) accounts for interreflections. The algorithm as such relies on the minimization of a three-component error term, which penalizes intensity deviations, integrability deviations, and deviations from the known large-scale surface shape. The solution of the error minimization is obtained iteratively based on a calculus of variations. BRDF parameters are estimated by initially reducing and then iteratively refining the optical resolution, which provides the required robust data basis. The 3D reconstruction of concave surface regions affected by interreflections is improved by compensating global illumination in the image data. The algorithm is evaluated based on eight objects with varying albedos and reflectance behaviors (diffuse, specular, metallic). The qualitative evaluation shows a removal of outliers and a strong reduction of noise, while the large scale shape is preserved. Fine surface details Which are previously not contained in the surface scans, are incorporated through using image data. The algorithm is evaluated with respect to its absolute accuracy using two caliper objects of known shape, and based on synthetically generated data. The beneficial effect of interreflection compensation on the reconstruction accuracy is evaluated quantitatively in a

An intensity ratio method for 3Dimaging is proposed with error analysis given for assessment and future improvements. The method is cheap and reasonably fast as it requires no mechanical scanning or laborious correspondence computation. One drawback of the intensity ratio methods which hamper their widespread use is the undesirable change of image intensity. This is usually caused by the difference in reflection from different parts of an object surface and the automatic iris or gain control of the camera. In our method, gray-level patterns used include an uniform pattern, a staircase pattern and a sawtooth pattern to make the system more robust against errors in intensity ratio. 3D information of the surface points of an object can be derived from the intensity ratios of the images by triangulation. A reference back plane is put behind the object to monitor the change in image intensity. Errors due to camera calibration, projector calibration, variations in intensity, imperfection of the slides etc. are analyzed. Early experiments of the system using a newvicon CCTV camera with back plane intensity correction gives a mean-square range error of about 0.5 percent. Extensive analysis of various errors is expected to yield methods for improving the accuracy.

The ability to image complex geologies such as salt domes in the Gulf of Mexico and thrusts in mountainous regions is a key to reducing the risk and cost associated with oil and gas exploration. Imaging these structures, however, is computationally expensive. Datasets can be terabytes in size, and the processing time required for the multiple iterations needed to produce a velocity model can take months, even with the massively parallel computers available today. Some algorithms, such as 3D, finite-difference, prestack, depth migration remain beyond the capacity of production seismic processing. Massively parallel processors (MPPs) and algorithms research are the tools that will enable this project to provide new seismic processing capabilities to the oil and gas industry. The goals of this work are to (1) develop finite-difference algorithms for 3D, prestack, depth migration; (2) develop efficient computational approaches for seismic imaging and for processing terabyte datasets on massively parallel computers; and (3) develop a modular, portable, seismic imaging code.

Over the years, many enhancements have been made by the oil and gas industry to improve the quality of seismic images. The GPR project at GTRI borrows heavily from these technologies in order to produce 3-D GPR images of PVC gas pipes. As will be demonstrated, improvements in GPR data acquisition, 3-D processing and visualization schemes yield good images of PVC pipes in the subsurface. Data have been collected in cooperation with the local gas company and at a test facility in Texas. Surveys were conducted over both a metal pipe and PVC pipes of diameters ranging from {1/2} in. to 4 in. at depths from 1 ft to 3 ft in different soil conditions. The metal pipe produced very good reflections and was used to fine tune and optimize the processing run stream. It was found that the following steps significantly improve the overall image: (1) Statics for drift and topography compensation, (2) Deconvolution, (3) Filtering and automatic gain control, (4) Migration for focusing and resolution, and (5) Visualization optimization. The processing flow implemented is relatively straightforward, simple to execute and robust under varying conditions. Future work will include testing resolution limits, effects of soil conditions, and leak detection.

Conventional 3D-TV codecs processing one down-compatible (either left, or right) channel may optionally include the extraction of the disparity field associated with the stereo-pairs to support the coding of the complementary channel. A two-fold improvement over such approaches is proposed in this paper by exploiting 3D features retained in the stereo-pairs to reduce the redundancies in both channels, and according to their visual sensitiveness. Through an a-priori disparity field analysis, our coding scheme separates a region of interest from the foreground/background in the volume space reproduced in order to code them selectively based on their visual relevance. Such a region of interest is here identified as the one which is focused by the shooting device. By suitably scaling the DCT coefficient n such a way that precision is reduced for the image blocks lying on less relevant areas, our approach aims at reducing the signal energy in the background/foreground patterns, while retaining finer details on the more relevant image portions. From an implementation point of view, it is worth noticing that the system proposed keeps its surplus processing power on the encoder side only. Simulation results show such improvements as a better image quality for a given transmission bit rate, or a graceful quality degradation of the reconstructed images with decreasing data-rates.

Ice shelves are sensitive indicators of climate change and play a critical role in the stability of ice sheets and oceanic currents. Basal melting of ice shelves plays an important role in both the mass balance of the ice sheet and the global climate system. Airborne- and satellite based remote sensing systems can perform thickness measurements of ice shelves. Time separated repeat flight tracks over ice shelves of interest generate data sets that can be used to derive basal melt rates using traditional glaciological techniques. Many previous melt rate studies have relied on surface elevation data gathered by airborne- and satellite based altimeters. These systems infer melt rates by assuming hydrostatic equilibrium, an assumption that may not be accurate, especially near an ice shelf's grounding line. Moderate bandwidth, VHF, ice penetrating radar has been used to measure ice shelf profiles with relatively coarse resolution. This study presents the application of an ultra wide bandwidth (UWB), UHF, ice penetrating radar to obtain finer resolution data on the ice shelves. These data reveal significant details about the basal interface, including the locations and depth of bottom crevasses and deviations from hydrostatic equilibrium. While our single channel radar provides new insight into ice shelf structure, it only images a small swatch of the shelf, which is assumed to be an average of the total shelf behavior. This study takes an additional step by investigating the application of a 3Dimaging technique to a data set collected using a ground based multi channel version of the UWB radar. The intent is to show that the UWB radar could be capable of providing a wider swath 3Dimage of an ice shelf. The 3Dimages can then be used to obtain a more complete estimate of the bottom melt rates of ice shelves.

Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a

In a previous system we showed how the three-dimensionality of an object can be projected and preserved on a diffractive screen, which is just a simple diffractive holographic lens. A transmission object is illuminated with an extended filament of a white light lamp and no additional element is necessary. The system forms three-dimensional (3D) images with normal depth (orthoscopic) of the shadow type. The continuous parallax, perfect sharpness and additional characteristics of the image depend on the width and extension of the luminous filament and the properties of the diffractive lens. This new imaging system is shown to inspire an interesting extension to non-perfect reflective or refractive imaging elements because the sharpness of the image depends only on the width of the source. As new light sources are being developed that may result in very thin linear white light sources, for example, light emitting diodes, it may be useful to further develop this technique. We describe an imaging process in which a rough Fresnel metallic mirror can give a sharp image of an object due to the reduced width of a long filament lamp. We will discuss how the process could be extended to Fresnel lenses or to any aberrating imaging element.

Three-dimensional (3D) microwave imaging reflectometry has been developed in the large helical device to visualize fluctuating reflection surface which is caused by the density fluctuations. The plasma is illuminated by the probe wave with four frequencies, which correspond to four radial positions. The imaging optics makes the image of cut-off surface onto the 2D (7 × 7 channels) horn antenna mixer arrays. Multi-channel receivers have been also developed using micro-strip-line technology to handle many channels at reasonable cost. This system is first applied to observe the edge harmonic oscillation (EHO), which is an MHD mode with many harmonics that appears in the edge plasma. A narrow structure along field lines is observed during EHO. PMID:23126965

The current high interest in 3-D ultrasound imaging is pushing the development of 2-D probes with a challenging number of active elements. The most popular approach to limit this number is the sparse array technique, which designs the array layout by means of complex optimization algorithms. These algorithms are typically constrained by a few steering conditions, and, as such, cannot guarantee uniform side-lobe performance at all angles. The performance may be improved by the ungridded extensions of the sparse array technique, but this result is achieved at the expense of a further complication of the optimization process. In this paper, a method to design the layout of large circular arrays with a limited number of elements according to Fermat's spiral seeds and spatial density modulation is proposed and shown to be suitable for application to 3-D ultrasound imaging. This deterministic, aperiodic, and balanced positioning procedure attempts to guarantee uniform performance over a wide range of steering angles. The capabilities of the method are demonstrated by simulating and comparing the performance of spiral and dense arrays. A good trade-off for small vessel imaging is found, e.g., in the 60λ spiral array with 1.0λ elements and Blackman density tapering window. Here, the grating lobe level is -16 dB, the lateral resolution is lower than 6λ the depth of field is 120λ and, the average contrast is 10.3dB, while the sensitivity remains in a 5 dB range for a wide selection of steering angles. The simulation results may represent a reference guide to the design of spiral sparse array probes for different application fields. PMID:26285181

A joint-service team led by the Air Force Research Laboratory's Munitions and Sensors Directorates completed a successful flight test demonstration of the 3D-LZ Helicopter LADAR Imaging System. This was a milestone demonstration in the development of technology solutions for a problem known as "helicopter brownout", the loss of situational awareness caused by swirling sand during approach and landing. The 3D-LZ LADAR was developed by H.N. Burns Engineering and integrated with the US Army Aeroflightdynamics Directorate's Brown-Out Symbology System aircraft state symbology aboard a US Army EH-60 Black Hawk helicopter. The combination of these systems provided an integrated degraded visual environment landing solution with landing zone situational awareness as well as aircraft guidance and obstacle avoidance information. Pilots from the U.S. Army, Air Force, Navy, and Marine Corps achieved a 77% landing rate in full brownout conditions at a test range at Yuma Proving Ground, Arizona. This paper will focus on the LADAR technology used in 3D-LZ and the results of this milestone demonstration.

A review of recent progress in colour holography is provided with new applications. Colour holography recording techniques in silver-halide emulsions are discussed. Both analogue, mainly Denisyuk colour holograms, and digitally-printed colour holograms are described and their recent improvements. An alternative to silver-halide materials are the panchromatic photopolymer materials such as the DuPont and Bayer photopolymers which are covered. The light sources used to illuminate the recorded holograms are very important to obtain ultra-realistic 3-Dimages. In particular the new light sources based on RGB LEDs are described. They show improved image quality over today's commonly used halogen lights. Recent work in colour holography by holographers and companies in different countries around the world are included. To record and display ultra-realistic 3-Dimages with perfect colour rendering are highly dependent on the correct recording technique using the optimal recording laser wavelengths, the availability of improved panchromatic recording materials and combined with new display light sources.

Summary There is a debate in the literature about the need for Computed Tomagraphy (CT) before removing third molars, even if positive radiographic signs are present. In few cases, the third molar is so close to the inferior alveolar nerve that its extraction might expose patients to the risk of post-operative neuro-sensitive alterations of the skin and the mucosa of the homolateral lower lip and chin. Thus, the injury of the inferior alveolar nerve may represent a serious, though infrequent, neurologic complication in the surgery of the third molars rendering necessary a careful pre-operative evaluation of their anatomical relationship with the inferior alveolar nerve by means of radiographic imaging techniques. This contribution presents two case reports showing positive radiographic signs, which are the hallmarks of a possible close relationship between the inferior alveolar nerve and the third molars. We aim at better defining the relationship between third molars and the mandibular canal using Dental CT Scan, DICOM image acquisition and 3D reconstruction with a dedicated software. By our study we deduce that 3Dimages are not indispensable, but they can provide a very agreeable assistance in the most complicated cases. PMID:23386934

Neutron detection and neutron flux assessment are important aspects in monitoring nuclear energy production. Neutron flux measurements can also provide information on potential biological damage from exposure. In addition to the applications for neutron measurement in nuclear energy, neutron detection has been proposed as a method of enhancing neutrino detectors and cosmic ray flux has also been assessed using ground-level neutron detectors. Solid State Nuclear Track Detectors (or SSNTDs) have been used extensively to examine cosmic rays, long-lived radioactive elements, radon concentrations in buildings and the age of geological samples. Passive SSNTDs consisting of a CR-39 plastic are commonly used to measure radon because they respond to incident charged particles such as alpha particles from radon gas in air. They have a large dynamic range and a linear flux response. We have previously applied confocal microscopy to obtain 3Dimages of alpha particle tracks in SSNTDs from radon track monitoring (1). As a charged particle traverses through the polymer it creates an ionisation trail along its path. The trail or track is normally enhanced by chemical etching to better expose radiation damage, as the damaged area is more sensitive to the etchant than the bulk material. Particle tracks in CR-39 are usually assessed using 2D optical microscopy. In this study 6 detectors were examined using an Olympus OLS4100 LEXT 3D laser scanning confocal microscope (Olympus Corporation, Japan). The detectors had been etched for 2 hours 50 minutes at 85 °C in 6.25M NaOH. Post etch the plastics had been treated with a 10 minute immersion in a 2% acetic acid stop bath, followed by rinsing in deionised water. The detectors examined had been irradiated with a 2mSv neutron dose from an Am(Be) neutron source (producing roughly 20 tracks per mm2). We were able to successfully acquire 3Dimages of neutron tracks in the detectors studied. The range of track diameter observed was between 4

In this paper, we describe a new 3D light propagation model aimed at understanding the effects of various physiological properties on subcutaneous vein imaging. In particular, we build upon the well known MCML (Monte Carlo Multi Layer) code and present a tissue model that improves upon the current state-of-the-art by: incorporating physiological variation, such as melanin concentration, fat content, and layer thickness; including veins of varying depth and diameter; using curved surfaces from real arm shapes; and modeling the vessel wall interface. We describe our model, present results from the Monte Carlo modeling, and compare these results with those obtained with other Monte Carlo methods.

Optical-CT has been shown to be a potentially useful imaging tool for the two very different spheres of biologists and radiation therapy physicists, but it has yet to live up to that potential. In radiation therapy, researchers have used optical-CT for the readout of 3D dosimeters, but it is yet to be a clinically relevant tool as the technology is too slow to be considered practical. Biologists have used the technique for structural imaging, but have struggled with emission tomography as the reality of photon attenuation for both excitation and emission have made the images quantitatively irrelevant. Dosimetry. The DLOS (Duke Large field of view Optical-CT Scanner) was designed and constructed to make 3D dosimetry utilizing optical-CT a fast and practical tool while maintaining the accuracy of readout of the previous, slower readout technologies. Upon construction/optimization/implementation of several components including a diffuser, band pass filter, registration mount & fluid filtration system the dosimetry system provides high quality data comparable to or exceeding that of commercial products. In addition, a stray light correction algorithm was tested and implemented. The DLOS in combination with the 3D dosimeter it was designed for, PREAGETM, then underwent rigorous commissioning and benchmarking tests validating its performance against gold standard data including a set of 6 irradiations. DLOS commissioning tests resulted in sub-mm isotropic spatial resolution (MTF >0.5 for frequencies of 1.5lp/mm) and a dynamic range of ˜60dB. Flood field uniformity was 10% and stable after 45minutes. Stray light proved to be small, due to telecentricity, but even the residual can be removed through deconvolution. Benchmarking tests showed the mean 3D passing gamma rate (3%, 3mm, 5% dose threshold) over the 6 benchmark data sets was 97.3% +/- 0.6% (range 96%-98%) scans totaling ˜10 minutes, indicating excellent ability to perform 3D dosimetry while improving the speed of

We have developed a fast 3D photoacoustic imaging system based on a sparse array of ultrasound detectors and iterative image reconstruction. To investigate the high frame rate capabilities of our system in the context of rotational motion, flow, and spectroscopy, we performed high frame-rate imaging on a series of targets, including a rotating graphite rod, a bolus of methylene blue flowing through a tube, and hyper-spectral imaging of a tube filled with methylene blue under a no flow condition. Our frame-rate for image acquisition was 10 Hz, which was limited by the laser repetition rate. We were able to track the rotation of the rod and accurately estimate its rotational velocity, at a rate of 0.33 rotations-per-second. The flow of contrast in the tube, at a flow rate of 180 μL/min, was also well depicted, and quantitative analysis suggested a potential method for estimating flow velocity from such measurements. The spectrum obtained did not provide accurate results, but depicted the spectral absorption signature of methylene blue , which may be sufficient for identification purposes. These preliminary results suggest that our high frame-rate photoacoustic imaging system could be used for identifying contrast agents and monitoring kinetics as an agent propagates through specific, simple structures such as blood vessels.

Minimally invasive partial nephrectomy (MIPN) is now considered the procedure of choice for small renal masses largely based on functional advantages over traditional open surgery. Lack of haptic feedback, the need for spatial understanding of tumor borders, and advanced operative techniques to minimize ischemia time or achieve zero-ischemia PN are among factors that make MIPN a technically demanding operation with a steep learning curve for inexperienced surgeons. Surgical simulation has emerged as a useful training adjunct in residency programs to facilitate the acquisition of these complex operative skills in the setting of restricted work hours and limited operating room time and autonomy. However, the majority of available surgical simulators focus on basic surgical skills, and procedure-specific simulation is needed for optimal surgical training. Advances in 3-dimensional (3-D) imaging have also enhanced the surgeon's ability to localize tumors intraoperatively. This article focuses on recent procedure-specific simulation models for laparoscopic and robotic-assisted PN and advanced 3-Dimaging techniques as part of pre- and some cases, intraoperative surgical planning. PMID:27314271

This paper presents the first fully automated reconstruction technique of 3D virtual colon segments from individual colonoscopy images. It is the basis of new software applications that may offer great benefits for improving quality of care for colonoscopy patients. For example, a 3D map of the areas inspected and uninspected during colonoscopy can be shown on request of the endoscopist during the procedure. The endoscopist may revisit the suggested uninspected areas to reduce the chance of missing polyps that reside in these areas. The percentage of the colon surface seen by the endoscopist can be used as a coarse objective indicator of the quality of the procedure. The derived virtual colon models can be stored for post-procedure training of new endoscopists to teach navigation techniques that result in a higher level of procedure quality. Our technique does not require a prior CT scan of the colon or any global positioning device. Our experiments on endoscopy images of an Olympus synthetic colon model reveal encouraging results with small average reconstruction errors (4.1 mm for the fold depths and 12.1 mm for the fold circumferences). PMID:24225230

The inspection of very large objects like sea freight containers with X-ray Computed Tomography (CT) is an emerging technology. A complete 3-D CT scan of a see-freight container takes several hours. Of course, this is too slow to apply it to a large number of containers. However, the benefits of a 3-D CT for sealed freight are obvious: detection of potential threats or illicit cargo without being confronted with legal complications or high time consumption and risks for the security personnel during a manual inspection. Recently distinct progress was made in the field of reconstruction of projections with only a relatively low number of angular positions. Instead of today's 500 to 1000 rotational steps, as needed for conventional CT reconstruction techniques, this new class of algorithms provides the potential to reduce the number of projection angles approximately by a factor of 10. The main drawback of these advanced iterative methods is the high consumption for numerical processing. But as computational power is getting steadily cheaper, there will be practical applications of these complex algorithms in a foreseeable future. In this paper, we discuss the properties of iterative image reconstruction algorithms and show results of their application to CT of extremely large objects scanning a sea-freight container. A specific test specimen is used to quantitatively evaluate the image quality in terms of spatial and contrast resolution and depending on different number of projections.

The inspection of very large objects like sea freight containers with X-ray Computed Tomography (CT) is an emerging technology. A complete 3-D CT scan of a see-freight container takes several hours. Of course, this is too slow to apply it to a large number of containers. However, the benefits of a 3-D CT for sealed freight are obvious: detection of potential threats or illicit cargo without being confronted with legal complications or high time consumption and risks for the security personnel during a manual inspection. Recently distinct progress was made in the field of reconstruction of projections with only a relatively low number of angular positions. Instead of today’s 500 to 1000 rotational steps, as needed for conventional CT reconstruction techniques, this new class of algorithms provides the potential to reduce the number of projection angles approximately by a factor of 10. The main drawback of these advanced iterative methods is the high consumption for numerical processing. But as computational power is getting steadily cheaper, there will be practical applications of these complex algorithms in a foreseeable future. In this paper, we discuss the properties of iterative image reconstruction algorithms and show results of their application to CT of extremely large objects scanning a sea-freight container. A specific test specimen is used to quantitatively evaluate the image quality in terms of spatial and contrast resolution and depending on different number of projections.

An approach for estimating 3D head orientation in a monocular image sequence is proposed. The approach employs recently developed image-based parameterized tracking for face and face features to locate the area in which a sub- pixel parameterized shape estimation of the eye's boundary is performed. This involves tracking of five points (four at the eye corners and the fifth is the tip of the nose). We describe an approach that relies on the coarse structure of the face to compute orientation relative to the camera plane. Our approach employs projective invariance of the cross-ratios of the eye corners and anthropometric statistics to estimate the head yaw, roll and pitch. Analytical and experimental results are reported.

Linear arrays of electrodes in conjunction with electrical impedance tomography have been used to spatially interrogate industrial processes that have only limited access for sensor placement. This paper explores the compromises that are to be expected when using a small number of vertically positioned linear arrays to facilitate 3Dimaging using electrical tomography. A configuration with three arrays is found to give reasonable results when compared with a 'conventional' arrangement of circumferential electrodes. A single array yields highly localized sensitivity that struggles to image the whole space. Strategies have been tested on a small-scale version of a sludge settling application that is of relevance to the industrial sponsor. A new electrode excitation strategy, referred to here as 'planar cross drive', is found to give superior results to an extended version of the adjacent electrodes technique due to the improved uniformity of the sensitivity across the domain. Recommendations are suggested for parameters to inform the scale-up to industrial vessels.

SAR imaging at low center frequencies (UHF and L-band) offers advantages over imaging at more conventional (X-band) frequencies, including foliage penetration for target detection and scene segmentation based on polarimetric coherency. However, bandwidths typically available at these center frequencies are small, affording poor resolution. By exploiting extreme spatial diversity (partial hemispheric k-space coverage) and nonlinear bandwidth extrapolation/interpolation methods such as Least-Squares SuperResolution (LSSR) and Least-Squares CLEAN (LSCLEAN), one can achieve resolutions that are commensurate with the carrier frequency (λ/4) rather than the bandwidth (c/2B). Furthermore, extreme angle diversity affords complete coverage of a target's backscatter, and a correspondingly more literal image. To realize these benefits, however, one must image the scene in 3-D; otherwise layover-induced misregistration compromises the coherent summation that yields improved resolution. Practically, one is limited to very sparse elevation apertures, i.e. a small number of circular passes. Here we demonstrate that both LSSR and LSCLEAN can reduce considerably the sidelobe and alias artifacts caused by these sparse elevation apertures. Further, we illustrate how a hypothetical multi-static geometry consisting of six vertical real-aperture receive apertures, combined with a single circular transmit aperture provide effective, though sparse and unusual, 3-D k-space support. Forward scattering captured by this geometry reveals horizontal scattering surfaces that are missed in monostatic backscattering geometries. This paper illustrates results based on LucernHammer UHF and L-band mono- and multi-static simulations of a backhoe.

We developed a prototype tabletop holographic display system. This system consists of the object recognition system and the spatial imaging system. In this paper, we describe the recognition system using an RFID tag and the 3D display system using a holographic technology. A 3D display system is useful technology for virtual reality, mixed reality and augmented reality. We have researched spatial imaging and interaction system. We have ever proposed 3D displays using the slit as a parallax barrier, the lenticular screen and the holographic optical elements(HOEs) for displaying active image 1,2,3. The purpose of this paper is to propose the interactive system using these 3Dimaging technologies. In this paper, the authors describe the interactive tabletop 3D display system. The observer can view virtual images when the user puts the special object on the display table. The key technologies of this system are the object recognition system and the spatial imaging display.

Knowing the interiors of comets and other primitive bodies is fundamental to our understanding of how planets formed. We have developed a Discovery-class mission formulation, Comet Radar Explorer (CORE), based on the use of previously flown planetary radar sounding techniques, with the goal of obtaining high resolution 3Dimages of the interior of a small primitive body. We focus on the Jupiter-Family Comets (JFCs) as these are among the most primitive bodies reachable by spacecraft. Scattered in from far beyond Neptune, they are ultimate targets of a cryogenic sample return mission according to the Decadal Survey. Other suitable targets include primitive NEOs, Main Belt Comets, and Jupiter Trojans. The approach is optimal for small icy bodies ~3-20 km diameter with spin periods faster than about 12 hours, since (a) navigation is relatively easy, (b) radar penetration is global for decameter wavelengths, and (c) repeated overlapping ground tracks are obtained. The science mission can be as short as ~1 month for a fast-rotating JFC. Bodies smaller than ~1 km can be globally imaged, but the navigation solutions are less accurate and the relative resolution is coarse. Larger comets are more interesting, but radar signal is unlikely to be reflected from depths greater than ~10 km. So, JFCs are excellent targets for a variety of reasons. We furthermore focus on the use of Solar Electric Propulsion (SEP) to rendezvous shortly after the comet's perihelion. This approach leaves us with ample power for science operations under dormant conditions beyond ~2-3 AU. This leads to a natural mission approach of distant observation, followed by closer inspection, terminated by a dedicated radar mapping orbit. Radar reflections are obtained from a polar orbit about the icy nucleus, which spins underneath. Echoes are obtained from a sounder operating at dual frequencies 5 and 15 MHz, with 1 and 10 MHz bandwidths respectively. The dense network of echoes is used to obtain global 3D

Many questions in developmental biology depend on measuring the position and movement of individual cells within developing embryos. Yet, tools that provide this data are often challenged by high cell density and their accuracy is difficult to measure. Here, we present a three-step procedure to address this problem. Step one is a novel segmentation algorithm based on image derivatives that, in combination with selective post-processing, reliably and automatically segments cell nuclei from images of densely packed tissue. Step two is a quantitative validation using synthetic images to ascertain the efficiency of the algorithm with respect to signal-to-noise ratio and object density. Finally, we propose an original method to generate reliable and experimentally faithful ground truth datasets: Sparse-dense dual-labeled embryo chimeras are used to unambiguously measure segmentation errors within experimental data. Together, the three steps outlined here establish a robust, iterative procedure to fine-tune image analysis algorithms and microscopy settings associated with embryonic 3Dimage data sets. PMID:27332860

Biometrics is a rapidly evolving scientific and applied discipline that studies possible ways of personal identification by means of unique biological characteristics. Such identification is important in various situations requiring restricted access to certain areas, information and personal data and for cases of medical emergencies. A number of automated biometric techniques have been developed, including fingerprint, hand shape, eye and facial recognition, thermographic imaging, etc. All these techniques differ in the recognizable parameters, usability, accuracy and cost. Among these, fingerprint recognition stands alone since a very large database of fingerprints has already been acquired. Also, fingerprints are key evidence left at a crime scene and can be used to indentify suspects. Therefore, of all automated biometric techniques, especially in the field of law enforcement, fingerprint identification seems to be the most promising. We introduce a newer development of the ultrasonic fingerprint imaging. The proposed method obtains a scan only once and then varies the C-scan gate position and width to visualize acoustic reflections from any appropriate depth inside the skin. Also, B-scans and A-scans can be recreated from any position using such data array, which gives the control over the visualization options. By setting the C-scan gate deeper inside the skin, distribution of the sweat pores (which are located along the ridges) can be easily visualized. This distribution should be unique for each individual so this provides a means of personal identification, which is not affected by any changes (accidental or intentional) of the fingers' surface conditions. This paper discusses different setups, acoustic parameters of the system, signal and image processing options and possible ways of 3-dimentional visualization that could be used as a recognizable characteristic in biometric identification.

This report examines the feasibility and potential problems in developing a real-time ultrasonic flow imaging instrument for on-line monitoring of mixed-phased flows such as coal slurries. State-of-the-art ultrasonicimaging techniques are assessed for this application. Reflection and diffraction tomographies are proposed for further development, including image-reconstruction algorithms and parallel processing systems. A conventional ultrasonic C-scan technique is used to demonstrate the feasibility of imaging the particle motion in a solid/water flow. 13 refs., 11 figs.

Vector acoustic data has two more dimensions of information than pressure data and may allow for 3D underwater imaging with much less data than with hydrophone data. The vector acoustic sensors measures the particle motions due to passing sound waves and, in conjunction with a collocated hydrophone, the direction of travel of the sound waves. When using a controlled source with known source and sensor locations, the reflection points of the sound field can be determined with a simple trigonometric calculation. I demonstrate this concept with an experiment that used an accelerometer based vector acoustic sensor in a water tank with a short-pulse source and passive scattering targets. The sensor consists of a three-axis accelerometer and a matched hydrophone. The sound source was a standard transducer driven by a short 7 kHz pulse. The sensor was suspended in a fixed location and the hydrophone was moved about the tank by a robotic arm to insonify the tank from many locations. Several floats were placed in the tank as acoustic targets at diagonal ranges of approximately one meter. The accelerometer data show the direct source wave as well as the target scattered waves and reflections from the nearby water surface, tank bottom and sides. Without resorting to the usual methods of seismic imaging, which in this case is only two dimensional and relied entirely on the use of a synthetic source aperture, the two targets, the tank walls, the tank bottom, and the water surface were imaged. A directional ambiguity inherent to vector sensors is removed by using collocated hydrophone data. Although this experiment was in a very simple environment, it suggests that 3-D seismic surveys may be achieved with vector sensors using the same logistics as a 2-D survey that uses conventional hydrophones. This work was supported by the Office of Naval Research, program element 61153N.

Three-dimensional (3D) imaging has received increasingly extensive attention and has been widely used currently. Lots of efforts have been put on three-dimensional imaging method and system study, in order to meet fast and high accurate requirement. In this article, we realize a fast and high quality stereo matching algorithm on field programmable gate array (FPGA) using the combination of time-of-flight (TOF) camera and binocular camera. Images captured from the two cameras own a same spatial resolution, letting us use the depth maps taken by the TOF camera to figure initial disparity. Under the constraint of the depth map as the stereo pairs when comes to stereo matching, expected disparity of each pixel is limited within a narrow search range. In the meanwhile, using field programmable gate array (FPGA, altera cyclone IV series) concurrent computing we can configure multi core image matching system, thus doing stereo matching on embedded system. The simulation results demonstrate that it can speed up the process of stereo matching and increase matching reliability and stability, realize embedded calculation, expand application range.

The anatomic and functional localization of brain lesions for neurologic diagnosis and brain surgery is facilitated by labeling the cortical surface in 3Dimages. This paper presents a method which extracts cortical contours from magnetic resonance (MR) image series and then produces a planar surface map which preserves important anatomic features. The resultant map may be used for manual anatomic localization as well as for further automatic labeling. Outer contours are determined on MR cross-sectional images by following the clear boundaries between gray matter and cerebral-spinal fluid, skipping over sulci. Carrying this contour below the surface by shrinking it along its normal produces an inner contour that alternately intercepts gray matter (sulci) and white matter along its length. This procedure is applied to every section in the set, and the image (grayscale) values along the inner contours are radially projected and interpolated onto a semi-cylindrical surface with axis normal to the slices and large enough to cover the whole brain. A planar map of the cortical surface results by flattening this cylindrical surface. The projection from inner contour to cylindrical surface is unique in the sense that different points on the inner contour correspond to different points on the cylindrical surface. As the outer contours are readily obtained by automatic segmentation, cortical maps can be made directly from an MR series.

This paper investigates an algorithm for forming 3Dimages of the subsurface using stepped-frequency GPR data. The algorithm is specifically designed for a handheld GPR and therefore accounts for the irregular sampling pattern in the data and the spatially-variant air-ground interface by estimating an effective "ground-plane" and then registering the data to the plane. The algorithm efficiently solves the 4th-order polynomial for the Snell reflection points using a fully vectorized iterative scheme. The forward operator is implemented efficiently using an accelerated nonuniform FFT (Greengard and Lee, 2004); the adjoint operator is implemented efficiently using an interpolation step coupled with an upsampled FFT. The imaging is done as a linearized version of the full inverse problem, which is regularized using a sparsity constraint to reduce sidelobes and therefore improve image localization. Applying an appropriate sparsity constraint, the algorithm is able to eliminate most the surrounding clutter and sidelobes, while still rendering valuable image properties such as shape and size. The algorithm is applied to simulated data, controlled experimental data (made available by Dr. Waymond Scott, Georgia Institute of Technology), and government-provided data with irregular sampling and air-ground interface.

Linearized methods are presented for appraising image resolution and parameter accuracy in images generated with two and three dimensional non-linear electromagnetic inversion schemes. When direct matrix inversion is employed, the model resolution and model covariance matrices can be directly calculated. The columns of the model resolution matrix are shown to yield empirical estimates of the horizontal and vertical resolution throughout the imaging region. Plotting the square root of the diagonal of the model covariance matrix yields an estimate of how the estimated data noise maps into parameter error. When the conjugate gradient method is employed rather than a direct inversion technique (for example in 3D inversion), an iterative method can be applied to statistically estimate the model covariance matrix, as well as a regularization covariance matrix. The latter estimates the error in the inverted results caused by small variations in the regularization parameter. A method for calculating individual columns of the model resolution matrix using the conjugate gradient method is also developed. Examples of the image analysis techniques are provided on a synthetic cross well EM data set.

We introduce a new model-based approach for the segmentation of the thoracic aorta and its main branches from follow-up pediatric 3D MRA image data. For robust segmentation of vessels even in difficult cases (e.g., neighboring structures), we propose a new extended parametric cylinder model which requires only relatively few model parameters. The new model is used in conjunction with a two-step fitting scheme for refining the segmentation result yielding an accurate segmentation of the vascular shape. Moreover, we include a novel adaptive background masking scheme and we describe a spatial normalization scheme to align the segmentation results from follow-up examinations. We have evaluated our proposed approach using different 3D synthetic images and we have successfully applied the approach to follow-up pediatric 3D MRA image data.

Spectrotomography based on the scanning transmission x-ray microscope (STXM) at the 10ID-1 spectromicroscopy beamline of the Canadian Light Source was used to study two selected unicellular microorganisms. Spatial distributions of sulphur globules, calcium, protein, and polysaccharide in sulphur-metabolizing bacteria (Allochromatium vinosum) were determined at the S 2p, C 1s, and Ca 2p edges. 3D chemical mapping showed that the sulphur globules are located inside the bacteria with a strong spatial correlation with calcium ions (it is most probably calcium carbonate from the medium; however, with STXM the distribution and localization in the cell can be made visible, which is very interesting for a biologist) and polysaccharide-rich polymers, suggesting an influence of the organic components on the formation of the sulphur and calcium deposits. A second study investigated copper accumulating in yeast cells (Saccharomyces cerevisiae) treated with copper sulphate. 3D elemental imaging at the Cu 2p edge showed that Cu(II) is reduced to Cu(I) on the yeast cell wall. A novel needle-like wet cell sample holder for STXM spectrotomography studies of fully hydrated samples is discussed.

The first and perhaps most important phase of a surgical procedure is the insertion of an intravenous (IV) catheter. Currently, this is performed manually by trained personnel. In some visions of future operating rooms, however, this process is to be replaced by an automated system. Experiments to determine the best NIR wavelengths to optimize vein contrast for physiological differences such as skin tone and/or the presence of hair on the arm or wrist surface are presented. For illumination our system is composed of a mercury arc lamp coupled to a 10nm band-pass spectrometer. A structured lighting system is also coupled to our multispectral system in order to provide 3D information of the patient arm orientation. Images of each patient arm are captured under every possible combinations of illuminants and the optimal combination of wavelengths for a given subject to maximize vein contrast using linear discriminant analysis is determined. PMID:19582050

Structured light 3D surface imaging has been crucial in the fields of image processing and computer vision, particularly in reconstruction, recognition and others. In this dissertation, we propose the approaches to development of an efficient 3D surface imaging system using structured light patterns including reconstruction, recognition and sampling criterion. To achieve an efficient reconstruction system, we address the problem in its many dimensions. In the first, we extract geometric 3D coordinates of an object which is illuminated by a set of concentric circular patterns and reflected to a 2D image plane. The relationship between the original and the deformed shape of the light patterns due to a surface shape provides sufficient 3D coordinates information. In the second, we consider system efficiency. The efficiency, which can be quantified by the size of data, is improved by reducing the number of circular patterns to be projected onto an object of interest. Akin to the Shannon-Nyquist Sampling Theorem, we derive the minimum number of circular patterns which sufficiently represents the target object with no considerable information loss. Specific geometric information (e.g. the highest curvature) of an object is key to deriving the minimum sampling density. In the third, the object, represented using the minimum number of patterns, has incomplete color information (i.e. color information is given a priori along with the curves). An interpolation is carried out to complete the photometric reconstruction. The results can be approximately reconstructed because the minimum number of the patterns may not exactly reconstruct the original object. But the result does not show considerable information loss, and the performance of an approximate reconstruction is evaluated by performing recognition or classification. In an object recognition, we use facial curves which are deformed circular curves (patterns) on a target object. We simply carry out comparison between the

X-ray laminography is a powerful technique for quality control of semiconductor components. Despite the advantages of nondestructive 3Dimaging over 2D techniques based on sectioning, the acquisition time is still a major obstacle for practical use of the technique. In this paper, we consider the application of Discrete Tomography to laminography data, which can potentially reduce the scanning time while still maintaining a high reconstruction quality. By incorporating prior knowledge in the reconstruction algorithm about the materials present in the scanned object, far more accurate reconstructions can be obtained from the same measured data compared to classical reconstruction methods. We present a series of simulation experiments that illustrate the potential of the approach.

X-ray laminography is a powerful technique for quality control of semiconductor components. Despite the advantages of nondestructive 3Dimaging over 2D techniques based on sectioning, the acquisition time is still a major obstacle for practical use of the technique. In this paper, we consider the application of Discrete Tomography to laminography data, which can potentially reduce the scanning time while still maintaining a high reconstruction quality. By incorporating prior knowledge in the reconstruction algorithm about the materials present in the scanned object, far more accurate reconstructions can be obtained from the same measured data compared to classical reconstruction methods. We present a series of simulation experiments that illustrate the potential of the approach.

Medical ultrasonicimaging system designed to provide quantitative data on various flows of blood in chambers, blood vessels, muscles, and tissues of heart. Sensitive enough to yield readings on flows of blood in heart even when microspheres used as ultrasonic contrast agents injected far from heart and diluted by circulation of blood elsewhere in body.

Piriformis syndrome is a pain syndrome originating in the buttock and is attributed to 6% - 8% of patients referred for the treatment of back and leg pain. The treatment for piriformis syndrome using fluoroscopy, computed tomography (CT), electromyography (EMG), and ultrasound (US) has become standard practice. The treatment of Piriformis Syndrome has evolved to include fluoroscopy and EMG with CT guidance. We present a case study of 5 successful piriformis injections using 3-D computer-assisted electromagnet needle tracking coupled with ultrasound. A 6-degree of freedom electromagnetic position tracker was attached to the ultrasound probe that allowed the system to detect the position and orientation of the probe in the magnetic field. The tracked ultrasound probe was used to find the posterior superior iliac spine. Subsequently, 3 points were captured to register the ultrasound image with the CT or magnetic resonance image scan. Moreover, after the registration was obtained, the navigation system visualized the tracked needle relative to the CT scan in real-time using 2 orthogonal multi-planar reconstructions centered at the tracked needle tip. Conversely, a recent study revealed that fluoroscopically guided injections had 30% accuracy compared to ultrasound guided injections, which tripled the accuracy percentage. This novel technique exhibited an accurate needle guidance injection precision of 98% while advancing to the piriformis muscle and avoiding the sciatic nerve. The mean (± SD) procedure time was 19.08 (± 4.9) minutes. This technique allows for electromagnetic instrument tip tracking with real-time 3-D guidance to the selected target. As with any new technique, a learning curve is expected; however, this technique could offer an alternative, minimizing radiation exposure. PMID:23703429

The raw computational power of GPU accelerators enables fast denoising of 3D MR images using bilateral filtering, anisotropic diffusion, and non-local means. In practice, applying these filtering operations requires setting multiple parameters. This study was designed to provide better guidance to practitioners for choosing the most appropriate parameters by answering two questions: what parameters yield the best denoising results in practice? And what tuning is necessary to achieve optimal performance on a modern GPU? To answer the first question, we use two different metrics, mean squared error (MSE) and mean structural similarity (MSSIM), to compare denoising quality against a reference image. Surprisingly, the best improvement in structural similarity with the bilateral filter is achieved with a small stencil size that lies within the range of real-time execution on an NVIDIA Tesla M2050 GPU. Moreover, inappropriate choices for parameters, especially scaling parameters, can yield very poor denoising performance. To answer the second question, we perform an autotuning study to empirically determine optimal memory tiling on the GPU. The variation in these results suggests that such tuning is an essential step in achieving real-time performance. These results have important implications for the real-time application of denoising to MR images in clinical settings that require fast turn-around times.

In this paper we present our Spectral LADAR concept, an augmented implementation of traditional LADAR. This sensor uses a polychromatic source to obtain range-resolved 3D spectral images which are used to identify objects based on combined spatial and spectral features, resolving positions in three dimensions and up to hundreds of meters in distance. We report on a proof-of-concept Spectral LADAR demonstrator that generates spectral point clouds from static scenes. The demonstrator transmits nanosecond supercontinuum pulses generated in a photonic crystal fiber. Currently we use a rapidly tuned receiver with a high-speed InGaAs APD for 25 spectral bands with the future expectation of implementing a linear APD array spectrograph. Each spectral band is independently range resolved with multiple return pulse recognition. This is a critical feature, enabling simultaneous spectral and spatial unmixing of partially obscured objects when not achievable using image fusion of monochromatic LADAR and passive spectral imagers. This enables higher identification confidence in highly cluttered environments such as forested or urban areas (e.g. vehicles behind camouflage or foliage). These environments present challenges for situational awareness and robotic perception which can benefit from the unique attributes of Spectral LADAR. Results from this demonstrator unit are presented for scenes typical of military operations and characterize the operation of the device. The results are discussed here in the context of autonomous vehicle navigation and target recognition.

The current definitive diagnosis of prostate cancer is transrectal ultrasound (TRUS) guided biopsy. However, the current procedure is limited by using 2D biopsy tools to target 3D biopsy locations. This paper presents a new method for automatic segmentation of the prostate in three-dimensional transrectal ultrasound images, by extracting texture features and by statistically matching geometrical shape of the prostate. A set of Wavelet-based support vector machines (WSVMs) are located and trained at different regions of the prostate surface. The WSVMs capture texture priors of ultrasound images for classification of the prostate and non-prostate tissues in different zones around the prostate boundary. In the segmentation procedure, these W-SVMs are trained in three sagittal, coronal, and transverse planes. The pre-trained W-SVMs are employed to tentatively label each voxel around the surface of the model as a prostate or non-prostate voxel by the texture matching. The labeled voxels in three planes after post-processing is overlaid on a prostate probability model. The probability prostate model is created using 10 segmented prostate data. Consequently, each voxel has four labels: sagittal, coronal, and transverse planes and one probability label. By defining a weight function for each labeling in each region, each voxel is labeled as a prostate or non-prostate voxel. Experimental results by using real patient data show the good performance of the proposed model in segmenting the prostate from ultrasound images.

20 Mega-Hertz-switching high speed image shutter device for 3Dimage capturing and its application to system prototype are presented. For 3Dimage capturing, the system utilizes Time-of-Flight (TOF) principle by means of 20MHz high-speed micro-optical image modulator, so called 'optical shutter'. The high speed image modulation is obtained using the electro-optic operation of the multi-layer stacked structure having diffractive mirrors and optical resonance cavity which maximizes the magnitude of optical modulation. The optical shutter device is specially designed and fabricated realizing low resistance-capacitance cell structures having small RC-time constant. The optical shutter is positioned in front of a standard high resolution CMOS image sensor and modulates the IR image reflected from the object to capture a depth image. Suggested novel optical shutter device enables capturing of a full HD depth image with depth accuracy of mm-scale, which is the largest depth image resolution among the-state-of-the-arts, which have been limited up to VGA. The 3D camera prototype realizes color/depth concurrent sensing optical architecture to capture 14Mp color and full HD depth images, simultaneously. The resulting high definition color/depth image and its capturing device have crucial impact on 3D business eco-system in IT industry especially as 3Dimage sensing means in the fields of 3D camera, gesture recognition, user interface, and 3D display. This paper presents MEMS-based optical shutter design, fabrication, characterization, 3D camera system prototype and image test results.

Recent development in optical 3D surface imaging technologies provide better ways to digitalize the 3D surface and its motion in real-time. The non-invasive 3D surface imaging approach has great potential for many medical imaging applications, such as motion monitoring of radiotherapy, pre/post evaluation of plastic surgery and dermatology, to name a few. Various commercial 3D surface imaging systems have appeared on the market with different dimension, speed and accuracy. For clinical applications, the accuracy, reproducibility and robustness across the widely heterogeneous skin color, tone, texture, shape properties, and ambient lighting is very crucial. Till now, a systematic approach for evaluating the performance of different 3D surface imaging systems still yet exist. In this paper, we present a systematic performance assessment approach to 3D surface imaging system assessment for medical applications. We use this assessment approach to exam a new real-time surface imaging system we developed, dubbed "Neo3D Camera", for image-guided radiotherapy (IGRT). The assessments include accuracy, field of view, coverage, repeatability, speed and sensitivity to environment, texture and color.

Purpose: Microbeam radiation therapy (MRT) techniques are under investigation at synchrotrons worldwide. Favourable outcomes from animal and cell culture studies have proven the efficacy of MRT. The aim of MRT researchers currently is to progress to human clinical trials in the near future. The purpose of this study was to demonstrate the high resolution and 3Dimaging of synchrotron generated microbeams in PRESAGE® dosimeters using laser fluorescence confocal microscopy. Methods: Water equivalent PRESAGE® dosimeters were fabricated and irradiated with microbeams on the Imaging and Medical Beamline at the Australian Synchrotron. Microbeam arrays comprised of microbeams 25–50 μm wide with 200 or 400 μm peak-to-peak spacing were delivered as single, cross-fire, multidirectional, and interspersed arrays. Imaging of the dosimeters was performed using a NIKON A1 laser fluorescence confocal microscope. Results: The spatial fractionation of the MRT beams was clearly visible in 2D and up to 9 mm in depth. Individual microbeams were easily resolved with the full width at half maximum of microbeams measured on images with resolutions of as low as 0.09 μm/pixel. Profiles obtained demonstrated the change of the peak-to-valley dose ratio for interspersed MRT microbeam arrays and subtle variations in the sample positioning by the sample stage goniometer were measured. Conclusions: Laser fluorescence confocal microscopy of MRT irradiated PRESAGE® dosimeters has been validated in this study as a high resolution imaging tool for the independent spatial and geometrical verification of MRT beam delivery.

Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm, and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future

Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical imaging. In 2008, the National Cancer Institute began building the Quantitative Imaging Network (QIN) initiative with the goal of advancing quantitative imaging in the context of personalized therapy and evaluation of treatment response. Computerized analysis is an important component contributing to reproducibility and efficiency of the quantitative imaging techniques. The success of quantitative imaging is contingent on robust analysis methods and software tools to bring these methods from bench to bedside. 3D Slicer is a free open-source software application for medical image computing. As a clinical research tool, 3D Slicer is similar to a radiology workstation that supports versatile visualizations but also provides advanced functionality such as automated segmentation and registration for a variety of application domains. Unlike a typical radiology workstation, 3D Slicer is free and is not tied to specific hardware. As a programming platform, 3D Slicer facilitates translation and evaluation of the new quantitative methods by allowing the biomedical researcher to focus on the implementation of the algorithm and providing abstractions for the common tasks of data communication, visualization and user interface development. Compared to other tools that provide aspects of this functionality, 3D Slicer is fully open source and can be readily extended and redistributed. In addition, 3D Slicer is designed to facilitate the development of new functionality in the form of 3D Slicer extensions. In this paper, we present an overview of 3D Slicer as a platform for prototyping, development and evaluation of image analysis tools for clinical research applications. To illustrate the utility of the platform in the scope of QIN, we discuss several use cases of 3D Slicer by the existing QIN teams, and we elaborate on the future

Improving the resolution and specificity of current ultrasonicimaging technology can enhance its relevance to detection of early-stage breast cancers. Ultrasonic evaluation of breast lesions is desirable because it is quick, inexpensive, and does not expose the patient to potentially harmful ionizing radiation. Improved image quality and resolution enables earlier detection and more accurate diagnoses of tumors, thus reducing the number of biopsies performed, increasing treatment options, and lowering mortality, morbidity, and remission percentages. In this work, a novel ultrasonicimaging reconstruction method that exploits straight-ray migration is described. This technique, commonly used in seismic imaging, accounts for scattering more accurately than standard ultrasonic approaches, thus providing superior image resolution. A breast phantom with various inclusions is imaged using a pulse-echo approach. The data are processed using the ultrasonic migration method and results are compared to standard linear ultrasound and to x-ray computed tomography (CT) scans. For an ultrasonic frequency of 2.25 MHz, imaged inclusions and features of approximately 1mm are resolved, although better resolution is expected with minor modifications. Refinement of this application using other imaging techniques such as time-reversal mirrors (TRM), synthetic aperture focusing technique (SAFT), decomposition of the time reversal operator (DORT), and factorization methods is also briefly discussed.

Time of flight laser range finding, deep space communications and scanning video imaging are three applications requiring very low noise optical receivers to achieve detection of fast and weak optical signal. HgCdTe electrons initiated avalanche photodiodes (e-APDs) in linear multiplication mode is the detector of choice thanks to its high quantum efficiency, high gain at low bias, high bandwidth and low noise factor. In this project, a readout integrated circuit of hybrid e-APD focal plane array (FPA) with 100um pitch for 3D-LADAR was designed for gated optical receiver. The ROIC works at 77K, including unit cell circuit, column-level circuit, timing control, bias circuit and output driver. The unit cell circuit is a key component, which consists of preamplifier, correlated double Sampling (CDS), bias circuit and timing control module. Specially, the preamplifier used the capacitor feedback transimpedance amplifier (CTIA) structure which has two capacitors to offer switchable capacitance for passive/active dual mode imaging. The main circuit of column-level circuit is a precision Multiply-by-Two circuit which is implemented by switched-capacitor circuit. Switched-capacitor circuit is quite suitable for the signal processing of readout integrated circuit (ROIC) due to the working characteristics. The output driver uses a simply unity-gain buffer. Because the signal is amplified in column-level circuit, the amplifier in unity-gain buffer uses a rail-rail amplifier. In active imaging mode, the integration time is 80ns. Integrating current from 200nA to 4uA, this circuit shows the nonlinearity is less than 1%. In passive imaging mode, the integration time is 150ns. Integrating current from 1nA to 20nA shows the nonlinearity less than 1%.

The Middle-East has seen a recent boom in construction including the planning and development of complete new sub-sections of metropolitan areas. Before planning and construction can commence, however, the development areas need to be investigated to determine their suitability for the planned project. Subsurface parameters such as the type of material (soil/rock), thickness of top soil or rock layers, depth and elastic parameters of basement, for example, comprise important information needed before a decision concerning the suitability of the site for construction can be made. A similar problem arises in environmental impact studies, when subsurface parameters are needed to assess the geological heterogeneity of the subsurface. Environmental impact studies are typically required for each construction project, particularly for the scale of the aforementioned building boom in the Middle East. The current study was conducted in Qatar at the location of a future highway interchange to evaluate a suite of 3D seismic techniques in their effectiveness to interrogate the subsurface for the presence of karst-like collapse structures. The survey comprised an area of approximately 10,000 m2 and consisted of 550 source- and 192 receiver locations. The seismic source was an accelerated weight drop while the geophones consisted of 3-component 10 Hz velocity sensors. At present, we analyzed over 100,000 P-wave phase arrivals and performed high-resolution 3-D tomographic imaging of the shallow subsurface. Furthermore, dispersion analysis of recorded surface waves will be performed to obtain S-wave velocity profiles of the subsurface. Both results, in conjunction with density estimates, will be utilized to determine the elastic moduli of the subsurface rock layers.

Today, development of slowly digestible food with positive health impact and production of biofuels is a matter of intense research. The latter is achieved via enzymatic hydrolysis of starch or biomass such as lignocellulose. Free label imaging, using UV autofluorescence, provides a great tool to follow one single enzyme when acting on a non-UV-fluorescent substrate. In this article, we report synchrotron DUV fluorescence in 3-dimensional imaging to visualize in situ the diffusion of enzymes on solid substrate. The degradation pathway of single starch granules by two amylases optimized for biofuel production and industrial starch hydrolysis was followed by tryptophan autofluorescence (excitation at 280 nm, emission filter at 350 nm). The new setup has been specially designed and developed for a 3D representation of the enzyme-substrate interaction during hydrolysis. Thus, this tool is particularly effective for improving knowledge and understanding of enzymatic hydrolysis of solid substrates such as starch and lignocellulosic biomass. It could open up the way to new routes in the field of green chemistry and sustainable development, that is, in biotechnology, biorefining, or biofuels. PMID:24796213

With advances in computer technology, it has become possible to create three-dimensional (3-D) images of anatomical structures for use in teaching gross anatomy. Reported is a survey of attitudes of 91 first-year medical students toward the use of 3-Dimages in their anatomy course. Reactions to the 3-Dimages and suggestions for improvement are…

An integral three-dimensional (3-D) system based on the principle of integral photography can display natural 3-Dimages. We studied ways of improving the resolution and viewing angle of 3-Dimages by using extremely highresolution (EHR) video in an integral 3-D video system. One of the problems with the EHR projection-type integral 3-D system is that positional errors appear between the elemental image and the elemental lens when there is geometric distortion in the projected image. We analyzed the relationships between the geometric distortion in the elemental images caused by the projection lens and the spatial distortion of the reconstructed 3-Dimage. As a result, we clarified that 3-Dimages reconstructed far from the lens array were greatly affected by the distortion of the elemental images, and that the 3-Dimages were significantly distorted in the depth direction at the corners of the displayed images. Moreover, we developed a video signal processor that electrically compensated the distortion in the elemental images for an EHR projection-type integral 3-D system. Therefore, the distortion in the displayed 3-Dimage was removed, and the viewing angle of the 3-Dimage was expanded to nearly double that obtained with the previous prototype system.

An infrared transmitting technique for 3D holographic images is studied. It seems to be very effective as a transmitting technique for 3D holographic images in the places where electric wave is prohibited to be used for transmission. In this paper, we first explain our infrared transmitting system for holograms and a display system for the presentation of holographic 3Dimages reconstructed from the received signal. Next, we make a report on the results obtained by infrared transmission of CGH and a comparison of the real and the reconstructed 3Dimages in our system. As this result, it is found that reconstructed holographic 3Dimages do not suffer a large deterioration in the quality and highly contrasted ones can be presented.

The field of discrete tomography focuses on the reconstruction of samples that consist of only a few different materials. Ideally, a three-dimensional (3D) reconstruction of such a sample should contain only one grey level for each of the compositions in the sample. By exploiting this property in the reconstruction algorithm, either the quality of the reconstruction can be improved significantly, or the number of required projection images can be reduced. The discrete reconstruction typically contains fewer artifacts and does not have to be segmented, as it already contains one grey level for each composition. Recently, a new algorithm, called discrete algebraic reconstruction technique (DART), has been proposed that can be used effectively on experimental electron tomography datasets. In this paper, we propose discrete tomography as a general reconstruction method for electron tomography in materials science. We describe the basic principles of DART and show that it can be applied successfully to three different types of samples, consisting of embedded ErSi(2) nanocrystals, a carbon nanotube grown from a catalyst particle and a single gold nanoparticle, respectively. PMID:19269094

Soil voids manifest the cumulative effect of local pedogenic processes and ultimately influence soil behavior - especially as it pertains to aeration and hydrophysical properties. Because of the relatively weak attenuation of X-rays by air, compared with liquids or solids, non-disruptive CT scanning has become a very attractive tool for generating three-dimensional imagery of soil voids. One of the main steps involved in this analysis is the thresholding required to transform the original (greyscale) images into the type of binary representation (e.g., pores in white, solids in black) needed for fractal analysis or simulation with Lattice-Boltzmann models (Baveye et al., 2010). The objective of the current work is to apply an innovative approach to quantifying soil voids and pore networks in original X-ray CT imagery using Relative Entropy (Bird et al., 2006; Tarquis et al., 2008). These will be illustrated using typical imagery representing contrasting soil structures. Particular attention will be given to the need to consider the full 3D context of the CT imagery, as well as scaling issues, in the application and interpretation of this index.

Among the main tasks of orthodontia are analysis of teeth arches and treatment planning for providing correct position for every tooth. The treatment plan is based on measurement of teeth parameters and designing perfect teeth arch curve which teeth are to create after treatment. The most common technique for teeth moving uses standard brackets which put on teeth and a wire of given shape which is clamped by these brackets for producing necessary forces to every tooth for moving it in given direction. The disadvantages of standard bracket technique are low accuracy of tooth dimensions measurements and problems with applying standard approach for wide variety of complex orthodontic cases. The image-based technique for orthodontic planning, treatment and documenting aimed at overcoming these disadvantages is proposed. The proposed approach provides performing accurate measurements of teeth parameters needed for adequate planning, designing correct teeth position and monitoring treatment process. The developed technique applies photogrammetric means for teeth arch 3D model generation, brackets position determination and teeth shifting analysis.

Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.

Endoscopic ultrasonicimaging system is an important component in the endoscopic ultrasonography system (EUS). Through the ultrasonic probe, the characteristics of the fault histology features of digestive organs is detected by EUS, and then received by the reception circuit which making up of amplifying, gain compensation, filtering and A/D converter circuit, in the form of ultrasonic echo. Endoscopic ultrasonicimaging system is the back-end processing system of the EUS, with the function of receiving digital ultrasonic echo modulated by the digestive tract wall from the reception circuit, acquiring and showing the fault histology features in the form of image and characteristic data after digital signal processing, such as demodulation, etc. Traditional endoscopic ultrasonicimaging systems are mainly based on image acquisition and processing chips, which connecting to personal computer with USB2.0 circuit, with the faults of expensive, complicated structure, poor portability, and difficult to popularize. To against the shortcomings above, this paper presents the methods of digital signal acquisition and processing specially based on embedded technology with the core hardware structure of ARM and FPGA for substituting the traditional design with USB2.0 and personal computer. With built-in FIFO and dual-buffer, FPGA implement the ping-pong operation of data storage, simultaneously transferring the image data into ARM through the EBI bus by DMA function, which is controlled by ARM to carry out the purpose of high-speed transmission. The ARM system is being chosen to implement the responsibility of image display every time DMA transmission over and actualizing system control with the drivers and applications running on the embedded operating system Windows CE, which could provide a stable, safe and reliable running platform for the embedded device software. Profiting from the excellent graphical user interface (GUI) and good performance of Windows CE, we can not

The routinely used procedure for evaluating tunnel positions following anterior cruciate ligament (ACL) reconstructions based on standard X-ray images is known to pose difficulties in terms of obtaining accurate measures, especially in providing three-dimensional tunnel positions. This is largely due to the variability in individual knee joint pose relative to X-ray plates. Accurate results were reported using postoperative CT. However, its extensive usage in clinical routine is hampered by its major requirement of having CT scans of individual patients, which is not available for most ACL reconstructions. These difficulties are addressed through the proposed method, which aligns a knee model to X-ray images using our novel single-image3D-2D registration method and then estimates the 3D tunnel position. In the proposed method, the alignment is achieved by using a novel contour-based 3D-2D registration method wherein image contours are treated as a set of oriented points. However, instead of using some form of orientation weighting function and multiplying it with a distance function, we formulate the 3D-2D registration as a probability density estimation using a mixture of von Mises-Fisher-Gaussian (vMFG) distributions and solve it through an expectation maximization (EM) algorithm. Compared with the ground-truth established from postoperative CT, our registration method in an experiment using a plastic phantom showed accurate results with errors of (-0.43°+/-1.19°, 0.45°+/-2.17°, 0.23°+/-1.05°) and (0.03+/-0.55, -0.03+/-0.54, -2.73+/-1.64) mm. As for the entry point of the ACL tunnel, one of the key measurements, it was obtained with high accuracy of 0.53+/-0.30 mm distance errors.

We present a novel general-purpose compression method for tomographic images, termed 3D adaptive sparse representation based compression (3D-ASRC). In this paper, we focus on applications of 3D-ASRC for the compression of ophthalmic 3D optical coherence tomography (OCT) images. The 3D-ASRC algorithm exploits correlations among adjacent OCT images to improve compression performance, yet is sensitive to preserving their differences. Due to the inherent denoising mechanism of the sparsity based 3D-ASRC, the quality of the compressed images are often better than the raw images they are based on. Experiments on clinical-grade retinal OCT images demonstrate the superiority of the proposed 3D-ASRC over other well-known compression methods. PMID:25561591

We present a novel general-purpose compression method for tomographic images, termed 3D adaptive sparse representation based compression (3D-ASRC). In this paper, we focus on applications of 3D-ASRC for the compression of ophthalmic 3D optical coherence tomography (OCT) images. The 3D-ASRC algorithm exploits correlations among adjacent OCT images to improve compression performance, yet is sensitive to preserving their differences. Due to the inherent denoising mechanism of the sparsity based 3D-ASRC, the quality of the compressed images are often better than the raw images they are based on. Experiments on clinical-grade retinal OCT images demonstrate the superiority of the proposed 3D-ASRC over other well-known compression methods. PMID:25561591

The goal of this dissertation is to explore the physics underpinning the use of quantitative acoustic measurements to extend the role of ultrasonicimaging. In the 30 year history of medical ultrasonicimaging, the diagnostic use of this modality has primarily relied upon morphology and motion to differentiate healthy from diseased tissue. Significant improvements in the bandwidth and dynamic range of clinical ultrasonicimaging systems in recent years offer the possibility of complementing existing qualitative information with truly quantitative information, derived from measurements of the acoustic properties of soft tissue. The phase velocity, attenuation coefficient, and backscatter coefficient are three such acoustic properties that are often employed to characterize the state of soft tissues. One goal of this dissertation was to investigate the reliability of these measurements, based on systematic laboratory studies performed on well-characterized tissue-mimicking media. To this end, quantitative measurements of the frequency dependence of phase velocity, attenuation coefficient, and backscatter coefficient were performed in tissue-mimicking phantoms as part of a national, multi-center study, sponsored by the American Institute of Ultrasound in Medicine. Both the intra- and inter-laboratory variability associated with these measurements were addressed. In addition to assessing the reproducibility of quantitative estimates of these acoustic parameters, this dissertation introduces and experimentally validates a novel measurement technique, based on the Kramers-Kronig dispersion relations, that improves the robustness of frequency domain phase velocity estimates in tissue-like media.

Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture. PMID:27136560

Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture. PMID:27136560

The understanding of wave propagation phenomena requires use of robust numerical models. 3D finite element (FE) models are generally prohibitively time consuming. However, advances in computing processor speed and memory allow them to be more and more competitive. In this context, EDF R&D developed the 3D version of the well-validated FE code ATHENA2D. The code is dedicated to the simulation of wave propagation in all kinds of elastic media and in particular, heterogeneous and anisotropic materials like welds. It is based on solving elastodynamic equations in the calculation zone expressed in terms of stress and particle velocities. The particularity of the code relies on the fact that the discretization of the calculation domain uses a Cartesian regular 3D mesh while the defect of complex geometry can be described using a separate (2D) mesh using the fictitious domains method. This allows combining the rapidity of regular meshes computation with the capability of modelling arbitrary shaped defects. Furthermore, the calculation domain is discretized with a quasi-explicit time evolution scheme. Thereby only local linear systems of small size have to be solved. The final step to reduce the computation time relies on the fact that ATHENA3D has been parallelized and adapted to the use of HPC resources. In this paper, the validation of the 3D FE model is discussed. A cross-validation of ATHENA 3D and CIVA is proposed for several inspection configurations. The performances in terms of calculation time are also presented in the cases of both local computer and computation cluster use.

3D spatial information from unmanned aerial vehicles (UAV) images is usually provided in the form of 3D point clouds. For various UAV applications, it is important to generate dense 3D point clouds automatically from over the entire extent of UAV images. In this paper, we aim to apply image matching for generation of local point clouds over a pair or group of images and global optimization to combine local point clouds over the whole region of interest. We tried to apply two types of image matching, an object space-based matching technique and an image space-based matching technique, and to compare the performance of the two techniques. The object space-based matching used here sets a list of candidate height values for a fixed horizontal position in the object space. For each height, its corresponding image point is calculated and similarity is measured by grey-level correlation. The image space-based matching used here is a modified relaxation matching. We devised a global optimization scheme for finding optimal pairs (or groups) to apply image matching, defining local match region in image- or object- space, and merging local point clouds into a global one. For optimal pair selection, tiepoints among images were extracted and stereo coverage network was defined by forming a maximum spanning tree using the tiepoints. From experiments, we confirmed that through image matching and global optimization, 3D point clouds were generated successfully. However, results also revealed some limitations. In case of image-based matching results, we observed some blanks in 3D point clouds. In case of object space-based matching results, we observed more blunders than image-based matching ones and noisy local height variations. We suspect these might be due to inaccurate orientation parameters. The work in this paper is still ongoing. We will further test our approach with more precise orientation parameters.

For identifying the pathological findings in MRIs, the anatomical structures in MRIs should be identified in advance. For studying the anatomical structures in MRIs, an education al tool that includes the horizontal, coronal, sagittal MRIs of entire body, corresponding segmented images, 3Dimages, and browsing software is necessary. Such an educational tool, however, is hard to obtain. Therefore, in this research, such an educational tool which helps medical students and doctors study the anatomical structures in MRIs was made as follows. A healthy, young Korean male adult with standard body shape was selected. Six hundred thirteen horizontal MRIs of the entire body were scanned and inputted to the personal computer. Sixty anatomical structures in the horizontal MRIs were segmented to make horizontal segmented images. Coronal, sagittal MRIs and coronal, sagittal segmented images were made. 3Dimages of anatomical structures in the segmented images were reconstructed by surface rendering method. Browsing software of the MRIs, segmented images, and 3Dimages was composed. This educational tool that includes horizontal, coronal, sagittal MRIs of entire body, corresponding segmented images, 3Dimages, and browsing software is expected to help medical students and doctors study anatomical structures in MRIs.

3Dimaging technique is very important and indispensable in diagnosis. The main stream of the technique is one in which 3Dimage is reconstructed from a set of slice images, such as X-ray CT and MRI. However, these systems require large space and high costs. On the other hand, a low cost and small size 3Dimaging system is needed in clinical veterinary medicine, for example, in the case of diagnosis in X-ray car or pasture area. We propose a novel 3Dimaging technique using 2-D X-ray radiographic images. This system can be realized by cheaper system than X-ray CT and enables to get 3Dimage in X-ray car or portable X-ray equipment. In this paper, a 3D visualization technique from 2-D radiographic images is proposed and several reconstructions are shown. These reconstructions are evaluated by veterinarians.

This article describes the equipment and software used to create facial 3Dimaging and discusses the validation and reliability of the objective assessments done using this equipment. By overlaying preoperative and postoperative 3Dimages, it is possible to assess the surgical changes in 3D. Methods are described to assess the 3D changes from the rhinoplasty techniques of nasal dorsal augmentation, increasing tip projection, narrowing the nose, and nasal lengthening. PMID:22004862

In this paper, we introduce the mobile embedded system implemented for capturing stereo image based on two CMOS camera module. We use WinCE as an operating system and capture the stereo image by using device driver for CMOS camera interface and Direct Draw API functions. We aslo comments on the GPU hardware and CUDA programming for implementation of 3D exaggeraion algorithm for ROI by adjusting and synthesizing the disparity value of ROI (region of interest) in real time. We comment on the pattern of aperture for deblurring of CMOS camera module based on the Kirchhoff diffraction formula and clarify the reason why we can get more sharp and clear image by blocking some portion of aperture or geometric sampling. Synthesized stereo image is real time monitored on the shutter glass type three-dimensional LCD monitor and disparity values of each segment are analyzed to prove the validness of emphasizing effect of ROI.

Recent advancements in computer technologies have propelled the development of 3Dimaging systems. 3D surface-imaging is taking surgeons to a new level of communication with patients; moreover, it provides quick and standardized image documentation. This article recounts the chronologic evolution of 3D surface imaging, and summarizes the current status of today's facial surface capturing technology. This article also discusses current 3D surface imaging hardware and software, and their different techniques, technologies, and scientific validation, which provides surgeons with the background information necessary for evaluating the systems and knowledge about the systems they might incorporate into their own practice. PMID:22004854

In this paper, a new software-oriented autostereoscopic 4-view imaging & display system for web-based 3Dimage communication is implemented by using 4 digital cameras, Intel Xeon server computer system, graphic card having four outputs, projection-type 4-view 3D display system and Microsoft' DirectShow programming library. And its performance is also analyzed in terms of image-grabbing frame rates, displayed image resolution, possible color depth and number of views. From some experimental results, it is found that the proposed system can display 4-view VGA images with a full color of 16bits and a frame rate of 15fps in real-time. But the image resolution, color depth, frame rate and number of views are mutually interrelated and can be easily controlled in the proposed system by using the developed software program so that, a lot of flexibility in design and implementation of the proposed multiview 3Dimaging and display system are expected in the practical application of web-based 3Dimage communication.

In this paper, we present a distributed fiber optic sensing scheme to study 3D strain fields inside concrete cubes during hydraulic fracturing process. Optical fibers embedded in concrete were used to monitor 3D strain field build-up with external hydraulic pressures. High spatial resolution strain fields were interrogated by the in-fiber Rayleigh backscattering with 1-cm spatial resolution using optical frequency domain reflectometry. The fiber optics sensor scheme presented in this paper provides scientists and engineers a unique laboratory tool to understand the hydraulic fracturing processes in various rock formations and its impacts to environments.

The technology to reliably transmit high-resolution visual imagery over short to medium distances in real time has led to the serious considerations of the use of telemedicine, telepresence, and telerobotics in the delivery of health care. These concepts may involve, and evolve toward: consultation from remote expert teaching centers; diagnosis; triage; real-time remote advice to the surgeon; and real-time remote surgical instrument manipulation (telerobotics with virtual reality). Further extrapolation leads to teledesign and telereplication of spare surgical parts through quantitative teleimaging of 3-D surfaces tied to CAD/CAM devices and an artificially intelligent archival data base of 'normal' shapes. The ability to generate 'topogrames' or 3-D surface numerical tables of coordinate values capable of creating computer-generated virtual holographic-like displays, machine part replication, and statistical diagnostic shape assessment is critical to the progression of telemedicine. Any virtual reality simulation will remain in 'video-game' realm until realistic dimensional and spatial relational inputs from real measurements in vivo during surgeries are added to an ever-growing statistical data archive. The challenges of managing and interpreting this 3-D data base, which would include radiographic and surface quantitative data, are considerable. As technology drives toward dynamic and continuous 3-D surface measurements, presenting millions of X, Y, Z data points per second of flexing, stretching, moving human organs, the knowledge base and interpretive capabilities of 'brilliant robots' to work as a surgeon's tireless assistants becomes imaginable. The brilliant robot would 'see' what the surgeon sees--and more, for the robot could quantify its 3-D sensing and would 'see' in a wider spectral range than humans, and could zoom its 'eyes' from the macro world to long-distance microscopy. Unerring robot hands could rapidly perform machine-aided suturing with

As an unique, unchangeable and easily acquired biometrics, fingerprint has been widely studied in academics and applied in many fields over the years. The traditional fingerprint recognition methods are based on the obtained 2D feature of fingerprint. However, fingerprint is a 3D biological characteristic. The mapping from 3D to 2D loses 1D information and causes nonlinear distortion of the captured fingerprint. Therefore, it is becoming more and more important to obtain 3D fingerprint information for recognition. In this paper, a novel 3D fingerprint imaging system is presented based on fringe projection technique to obtain 3D features and the corresponding color texture information. A series of color sinusoidal fringe patterns with optimum three-fringe numbers are projected onto a finger surface. From another viewpoint, the fringe patterns are deformed by the finger surface and captured by a CCD camera. 3D shape data of the finger can be obtained from the captured fringe pattern images. This paper studies the prototype of the 3D fingerprint imaging system, including principle of 3D fingerprint acquisition, hardware design of the 3Dimaging system, 3D calibration of the system, and software development. Some experiments are carried out by acquiring several 3D fingerprint data. The experimental results demonstrate the feasibility of the proposed 3D fingerprint imaging system.

Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3Dimage registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3Dimage registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |< 0.083 mm for translations and |mu| < 0.023 degrees for rotations. The precision sigma in x-, y-, and z-direction was 0.090, 0.077, and 0.220 mm for translations and 0.155 degrees , 0.243 degrees , and 0.074 degrees for rotations. Our results show that the accuracy and precision of in vitro IBRSA, performed under ideal laboratory conditions, are lower than in vitro standard RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications. PMID:17706656

Integral imaging (InI) is a 3D auto-stereoscopic technique that captures and displays 3Dimages. We present a method for easily projecting the information recorded with this technique by transforming the integral image into a plenoptic image, as well as choosing, at will, the field of view (FOV) and the focused plane of the displayed plenoptic image. Furthermore, with this method we can generate a sequence of images that simulates a camera travelling through the scene from a single integral image. The application of this method permits to improve the quality of 3D display images and videos.

New microscopes are needed to help realize the full potential of 3D organoid culture studies. In order to image large volumes of 3D organoid cultures while preserving the ability to catch every single cell, we propose a new imaging platform based on lensfree microscopy. We have built a lensfree diffractive tomography setup performing multi-angle acquisitions of 3D organoid culture embedded in Matrigel and developed a dedicated 3D holographic reconstruction algorithm based on the Fourier diffraction theorem. With this new imaging platform, we have been able to reconstruct a 3D volume as large as 21.5 mm3 of a 3D organoid culture of prostatic RWPE1 cells showing the ability of these cells to assemble in 3D intricate cellular network at the mesoscopic scale. Importantly, comparisons with 2D images show that it is possible to resolve single cells isolated from the main cellular structure with our lensfree diffractive tomography setup. PMID:27231600

New microscopes are needed to help realize the full potential of 3D organoid culture studies. In order to image large volumes of 3D organoid cultures while preserving the ability to catch every single cell, we propose a new imaging platform based on lensfree microscopy. We have built a lensfree diffractive tomography setup performing multi-angle acquisitions of 3D organoid culture embedded in Matrigel and developed a dedicated 3D holographic reconstruction algorithm based on the Fourier diffraction theorem. With this new imaging platform, we have been able to reconstruct a 3D volume as large as 21.5 mm (3) of a 3D organoid culture of prostatic RWPE1 cells showing the ability of these cells to assemble in 3D intricate cellular network at the mesoscopic scale. Importantly, comparisons with 2D images show that it is possible to resolve single cells isolated from the main cellular structure with our lensfree diffractive tomography setup. PMID:27231600

In this paper, human face classification using ultrasonic sonar imaging is investigated. On the basis of Freedman's “image pulse” model, the scattering centers model is employed to simplify the complex geometry of the human face into a series of scattering centers. A chirp signal is utilized to detect the human face for its high range resolution and large signal-to-noise ratio. Ultrasonic sonar images, also named high-resolution range profiles, are obtained by demodulating the echoes with a reference chirp signal. Features directly related to the geometry of the human face are extracted from ultrasonic sonar images and verified in the experiments designed with different configurations of transmitter-receiver (TR) pairs. Experimental results indicate that the improved feature extraction method can achieve a high recognition rate of over 99% in the case of ultrasonic transmitters angled at 45° above and orthogonal to the face, and this method improves the performance of ultrasonic face recognition compared with our previous result.

The transition regions at the edges of the ionospheric storm-enhanced density (SED) are important for a detailed understanding of the mid-latitude physical processes occurring during major magnetic storms. At the boundary, the density gradients are evidence of the drivers that link the larger processes of the SED, with its connection to the plasmasphere and prompt-penetration electric fields, to the smaller irregularities that result in scintillations. For this reason, we present our estimates of both the plasma variation with horizontal and vertical spatial scale of 10 - 100 km and the plasma motion within and along the edges of the SED. To estimate the density gradients, we use Ionospheric Data Assimilation Four-Dimensional (IDA4D), a mature data assimilation algorithm that has been developed over several years and applied to investigations of polar cap patches and space weather storms [Bust and Crowley, 2007; Bust et al., 2007]. We use the density specification produced by IDA4D with a new tool for deducing ionospheric drivers from 3D time-evolving electron density maps, called Estimating Model Parameters from Ionospheric Reverse Engineering (EMPIRE). The EMPIRE technique has been tested on simulated data from TIMEGCM-ASPEN and on IDA4D-based density estimates with ongoing validation from Arecibo ISR measurements [Datta-Barua et al., 2009a; 2009b]. We investigate the SED that formed during the geomagnetic super storm of November 20, 2003. We run IDA4D at low-resolution continent-wide, and then re-run it at high (~10 km horizontal and ~5-20 km vertical) resolution locally along the boundary of the SED, where density gradients are expected to be highest. We input the high-resolution estimates of electron density to EMPIRE to estimate the ExB drifts and field-aligned plasma velocities along the boundaries of the SED. We expect that these drivers contribute to the density structuring observed along the SED during the storm. Bust, G. S. and G. Crowley (2007

Aim. To determine whether 3D endoscopic images improved recognition accuracy for superficial gastrointestinal cancer compared with 2D images. Methods. We created an image catalog using 2D and 3Dimages of 20 specimens resected by endoscopic submucosal dissection. The twelve participants were allocated into two groups. Group 1 evaluated only 2D images at first, group 2 evaluated 3Dimages, and, after an interval of 2 weeks, group 1 next evaluated 3D and group 2 evaluated 2D images. The evaluation items were as follows: (1) diagnostic accuracy of the tumor extent and (2) confidence levels in assessing (a) tumor extent, (b) morphology, (c) microsurface structure, and (d) comprehensive recognition. Results. The use of 3Dimages resulted in an improvement in diagnostic accuracy in both group 1 (2D: 76.9%, 3D: 78.6%) and group 2 (2D: 79.9%, 3D: 83.6%), with no statistically significant difference. The confidence levels were higher for all items ((a) to (d)) when 3Dimages were used. With respect to experience, the degree of the improvement showed the following trend: novices > trainees > experts. Conclusions. By conversion into 3Dimages, there was a significant improvement in the diagnostic confidence level for superficial tumors, and the improvement was greater in individuals with lower endoscopic expertise. PMID:27597863

Aim. To determine whether 3D endoscopic images improved recognition accuracy for superficial gastrointestinal cancer compared with 2D images. Methods. We created an image catalog using 2D and 3Dimages of 20 specimens resected by endoscopic submucosal dissection. The twelve participants were allocated into two groups. Group 1 evaluated only 2D images at first, group 2 evaluated 3Dimages, and, after an interval of 2 weeks, group 1 next evaluated 3D and group 2 evaluated 2D images. The evaluation items were as follows: (1) diagnostic accuracy of the tumor extent and (2) confidence levels in assessing (a) tumor extent, (b) morphology, (c) microsurface structure, and (d) comprehensive recognition. Results. The use of 3Dimages resulted in an improvement in diagnostic accuracy in both group 1 (2D: 76.9%, 3D: 78.6%) and group 2 (2D: 79.9%, 3D: 83.6%), with no statistically significant difference. The confidence levels were higher for all items ((a) to (d)) when 3Dimages were used. With respect to experience, the degree of the improvement showed the following trend: novices > trainees > experts. Conclusions. By conversion into 3Dimages, there was a significant improvement in the diagnostic confidence level for superficial tumors, and the improvement was greater in individuals with lower endoscopic expertise. PMID:27597863

Purpose: To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Methods: Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Results: Volume measurement, using 3D US, shows a 2.8 {+-} 1.5% error, 4.4 {+-} 3.0% error for CT, and 3.1 {+-} 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. Conclusions: 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.

Segmentation of fluid-filled structures, such as the urinary bladder, from three-dimensional ultrasound images is necessary for measuring their volume. This paper describes a system for image enhancement, segmentation and volume measurement of fluid-filled structures on 3D ultrasound images. The system was applied for the measurement of urinary bladder volume. Results show an average error of less than 10% in the estimation of the total bladder volume.

The emergence of real-time 3D ultrasound (US) makes it possible to consider image-based tracking of subcutaneous soft tissue targets for computer guided diagnosis and therapy. We propose a 3D transrectal US based tracking system for precise prostate biopsy sample localisation. The aim is to improve sample distribution, to enable targeting of unsampled regions for repeated biopsies, and to make post-interventional quality controls possible. Since the patient is not immobilized, since the prostate is mobile and due to the fact that probe movements are only constrained by the rectum during biopsy acquisition, the tracking system must be able to estimate rigid transformations that are beyond the capture range of common image similarity measures. We propose a fast and robust multi-resolution attribute-vector registration approach that combines global and local optimization methods to solve this problem. Global optimization is performed on a probe movement model that reduces the dimensionality of the search space and thus renders optimization efficient. The method was tested on 237 prostate volumes acquired from 14 different patients for 3D to 3D and 3D to orthogonal 2D slices registration. The 3D-3D version of the algorithm converged correctly in 96.7% of all cases in 6.5s with an accuracy of 1.41mm (r.m.s.) and 3.84mm (max). The 3D to slices method yielded a success rate of 88.9% in 2.3s with an accuracy of 1.37mm (r.m.s.) and 4.3mm (max). PMID:18044549

3-D electrical resistivity surveys and inversion models are required to accurately resolve structures in areas with very complex geology where 2-D models might suffer from artefacts. Many 3-D surveys use a grid where the number of electrodes along one direction (x) is much greater than in the perpendicular direction (y). Frequently, due to limitations in the number of independent electrodes in the multi-electrode system, the surveys use a roll-along system with a small number of parallel survey lines aligned along the x-direction. The `Compare R' array optimization method previously used for 2-D surveys is adapted for such 3-D surveys. Offset versions of the inline arrays used in 2-D surveys are included in the number of possible arrays (the comprehensive data set) to improve the sensitivity to structures in between the lines. The array geometric factor and its relative error are used to filter out potentially unstable arrays in the construction of the comprehensive data set. Comparisons of the conventional (consisting of dipole-dipole and Wenner-Schlumberger arrays) and optimized arrays are made using a synthetic model and experimental measurements in a tank. The tests show that structures located between the lines are better resolved with the optimized arrays. The optimized arrays also have significantly better depth resolution compared to the conventional arrays.

We developed a cryomicrotome/imaging system that provides high resolution, high sensitivity block-face images of whole mice or excised organs, and applied it to a variety of biological applications. With this cryo-imaging system, we sectioned cryo-preserved tissues at 2-40 μm thickness and acquired high resolution brightfield and fluorescence images with microscopic in-plane resolution (as good as 1.2 μm). Brightfield images of normal and pathological anatomy show exquisite detail, especially in the abdominal cavity. Multi-planar reformatting and 3D renderings allow one to interrogate 3D structures. In this report, we present brightfield images of mouse anatomy, as well as 3D renderings of organs. For BPK mice model of polycystic kidney disease, we compared brightfield cryo-images and kidney volumes to MRI. The color images provided greater contrast and resolution of cysts as compared to in vivo MRI. We note that color cryo-images are closer to what a researcher sees in dissection, making it easier for them to interpret image data. The combination of field of view, depth of field, ultra high resolution and color/fluorescence contrast enables cryo-image volumes to provide details that cannot be found through in vivo imaging or other ex vivo optical imaging approaches. We believe that this novel imaging system will have applications that include identification of mouse phenotypes, characterization of diseases like blood vessel disease, kidney disease, and cancer, assessment of drug and gene therapy delivery and efficacy and validation of other imaging modalities.

We developed a three-dimensional (3D) segmentation method for transrectal ultrasound (TRUS) images, which is based on longitudinal image registration and machine learning. Using longitudinal images of each individual patient, we register previously acquired images to the new images of the same subject. Three orthogonal Gabor filter banks were used to extract texture features from each registered image. Patient-specific Gabor features from the registered images are used to train kernel support vector machines (KSVMs) and then to segment the newly acquired prostate image. The segmentation method was tested in TRUS data from five patients. The average surface distance between our and manual segmentation is 1.18 +/- 0.31 mm, indicating that our automatic segmentation method based on longitudinal image registration is feasible for segmenting the prostate in TRUS images.

A super-multiview condition simulator which can project up to four different view images to each eye is introduced. This simulator with the image having both disparity and perspective informs that the depth of field (DOF) will be extended to more than the default DOF values as the number of simultaneously but separately projected different view images to each eye increase. The DOF range can be extended to near 2 diopters with the four simultaneous view images. However, the DOF value increments are not prominent as the image with both disparity and perspective with the image with disparity only.

Purpose The purpose of this article is to present images from simulated breast microcalcifications and assess the pattern of the microcalcifications with a technical development called “depth 3-dimensional (D3D) augmented reality”. Materials and methods A computer, head display unit, joystick, D3D augmented reality software, and an in-house script of simulated data of breast microcalcifications in a ductal distribution were used. No patient data was used and no statistical analysis was performed. Results The D3D augmented reality system demonstrated stereoscopic depth perception by presenting a unique image to each eye, focal point convergence, head position tracking, 3D cursor, and joystick fly-through. Conclusion The D3D augmented reality imaging system offers image viewing with depth perception and focal point convergence. The D3D augmented reality system should be tested to determine its utility in clinical practice. PMID:27563261

We present a method of performing fast and accurate three-dimensional (3-D) backprojection using only Fourier transform operations for line-integral data acquired by planar detector arrays in positron emission tomography. This approach is a 3-D extension of the two-dimensional (2-D) linogram technique of Edholm. By using a special choice of parameters to index a line of response (LOR) for a pair of planar detectors, rather than the conventional parameters used to index a LOR for a circular tomograph, all the LORs passing through a point in the field of view (FOV) lie on a 2-D plane in the four-dimensional (4-D) data space. Thus, backprojection of all the LORs passing through a point in the FOV corresponds to integration of a 2-D plane through the 4-D "planogram." The key step is that the integration along a set of parallel 2-D planes through the planogram, that is, backprojection of a plane of points, can be replaced by a 2-D section through the origin of the 4-D Fourier transform of the data. Backprojection can be performed as a sequence of Fourier transform operations, for faster implementation. In addition, we derive the central-section theorem for planogram format data, and also derive a reconstruction filter for both backprojection-filtering and filtered-backprojection reconstruction algorithms. With software-based Fourier transform calculations we provide preliminary comparisons of planogram backprojection to standard 3-D backprojection and demonstrate a reduction in computation time by a factor of approximately 15. PMID:15084067

We present a flash trajectory imaging technique which can directly obtain target trajectory and realize non-contact measurement of motion parameters by range-gated imaging and time delay integration. Range-gated imaging gives the range of targets and realizes silhouette detection which can directly extract targets from complex background and decrease the complexity of moving target image processing. Time delay integration increases information of one single frame of image so that one can directly gain the moving trajectory. In this paper, we have studied the algorithm about flash trajectory imaging and performed initial experiments which successfully obtained the trajectory of a falling badminton. Our research demonstrates that flash trajectory imaging is an effective approach to imaging target trajectory and can give motion parameters of moving targets.

The aim of this study was to propose an algorithm for three-dimensional projection onto convex sets (3D POCS) to achieve super resolution reconstruction of 3D lung computer tomography (CT) images, and to introduce multi-resolution mixed display mode to make 3D visualization of pulmonary nodules. Firstly, we built the low resolution 3Dimages which have spatial displacement in sub pixel level between each other and generate the reference image. Then, we mapped the low resolution images into the high resolution reference image using 3D motion estimation and revised the reference image based on the consistency constraint convex sets to reconstruct the 3D high resolution images iteratively. Finally, we displayed the different resolution images simultaneously. We then estimated the performance of provided method on 5 image sets and compared them with those of 3 interpolation reconstruction methods. The experiments showed that the performance of 3D POCS algorithm was better than that of 3 interpolation reconstruction methods in two aspects, i.e., subjective and objective aspects, and mixed display mode is suitable to the 3D visualization of high resolution of pulmonary nodules. PMID:26710449

Echocardiography is a routine clinical procedure to diagnose cardiac functions. The organic structure of the mouse is similar to that of human so that murine echocardiography has potentially become an effective tool for the assessment of human cardiovascular disease. However, clinical ultrasonicimaging systems are not suitable for murine cardiac imaging due to its limited spatial and temporal resolution. Thus, high frequency ultrasonicimaging (≥ 20 MHz) is necessary in order to provide spatial resolution at the order of 100 μm. Furthermore, due to the lack of transducer arrays at such a high frequency, single-element transducer with mechanical scanning is typically used. Thus the frame rate is insufficient for imaging the quick motion of the mouse. In this paper, a high frequency ultrasonicimaging system with electrocardiography gating is built in order to provide both high spatial resolution and high temporal effecting resolution. The system utilizes the R-wave trigger signal from murine electrocardiography. Image data are acquired in either the block scanning mode or the line scanning mode. In block scanning, murine cardiac images in systole and diastole can be retrospectively reconstructed with a short data acquisition time. In line scanning, on the other hand, images during the entire cardiac cycle can be obtained. It is demonstrated that the effective frame rate can be up to 2 kHz, which is only limited by the pulse repetition rate of the system. PMID:17282556

A statistical model for the object and the complete image formation process in cryo electron microscopy of viruses is presented. Using this model, maximum likelihood reconstructions of the 3D structure of viruses are computed using the expectation maximization algorithm and an example based on Cowpea mosaic virus is provided.

Both mid-wave and long-wave IR cameras are used to measure various temperature profiles in thermoplastic parts as they are printed. Two significantly different 3D-printers are used in this study. The first is a small scale commercially available Solidoodle 3 printer, which prints parts with layer thicknesses on the order of 125μm. The second printer used is a "Big Area Additive Manufacturing" (BAAM) 3D-printer developed at Oak Ridge National Laboratory. The BAAM prints parts with a layer thicknesses of 4.06 mm. Of particular interest is the temperature of the previously deposited layer as the new hot layer is about to be extruded onto it. The two layers are expected have a stronger bond if the temperature of the substrate layer is above the glass transition temperature. This paper describes the measurement technique and results for a study of temperature decay and substrate layer temperature for ABS thermoplastic with and without the addition of chopped carbon fibers.

Objective quality assessment of distorted stereoscopic images is a challenging problem, especially when the distortions in the left and right views are asymmetric. Existing studies suggest that simply averaging the quality of the left and right views well predicts the quality of symmetrically distorted stereoscopic images, but generates substantial prediction bias when applied to asymmetrically distorted stereoscopic images. In this paper, we first build a database that contains both single-view and symmetrically and asymmetrically distorted stereoscopic images. We then carry out a subjective test, where we find that the quality prediction bias of the asymmetrically distorted images could lean toward opposite directions (overestimate or underestimate), depending on the distortion types and levels. Our subjective test also suggests that eye dominance effect does not have strong impact on the visual quality decisions of stereoscopic images. Furthermore, we develop an information content and divisive normalization-based pooling scheme that improves upon structural similarity in estimating the quality of single-view images. Finally, we propose a binocular rivalry-inspired multi-scale model to predict the quality of stereoscopic images from that of the single-view images. Our results show that the proposed model, without explicitly identifying image distortion types, successfully eliminates the prediction bias, leading to significantly improved quality prediction of the stereoscopic images. PMID:26087491

Fluorescence anisotropy imaging is a popular method to visualize changes in organization and conformation of biomolecules within cells and tissues. In such an experiment, depolarization effects resulting from differences in orientation, proximity and rotational mobility of fluorescently labeled molecules are probed with high spatial resolution. Fluorescence anisotropy is typically imaged using laser scanning and epifluorescence-based approaches. Unfortunately, those techniques are limited in either axial resolution, image acquisition speed, or by photobleaching. In the last decade, however, selective plane illumination microscopy has emerged as the preferred choice for three-dimensional time lapse imaging combining axial sectioning capability with fast, camera-based image acquisition, and minimal light exposure. We demonstrate how selective plane illumination microscopy can be utilized for three-dimensional fluorescence anisotropy imaging of live cells. We further examined the formation of focal adhesions by three-dimensional time lapse anisotropy imaging of CHO-K1 cells expressing an EGFP-paxillin fusion protein. PMID:26368202

Fluorescence anisotropy imaging is a popular method to visualize changes in organization and conformation of biomolecules within cells and tissues. In such an experiment, depolarization effects resulting from differences in orientation, proximity and rotational mobility of fluorescently labeled molecules are probed with high spatial resolution. Fluorescence anisotropy is typically imaged using laser scanning and epifluorescence-based approaches. Unfortunately, those techniques are limited in either axial resolution, image acquisition speed, or by photobleaching. In the last decade, however, selective plane illumination microscopy has emerged as the preferred choice for three-dimensional time lapse imaging combining axial sectioning capability with fast, camera-based image acquisition, and minimal light exposure. We demonstrate how selective plane illumination microscopy can be utilized for three-dimensional fluorescence anisotropy imaging of live cells. We further examined the formation of focal adhesions by three-dimensional time lapse anisotropy imaging of CHO-K1 cells expressing an EGFP-paxillin fusion protein. PMID:26368202

In this paper, we propose a new method that makes multi-layer images from a few viewpoint images to display a 3Dimage by the autostereoscopic display that has multiple display screens in the depth direction. We iterate simple "Shift and Subtraction" processes to make each layer image alternately. The image made in accordance with depth map like a volume slicing by gradations is used as the initial solution of iteration process. Through the experiments using the prototype stacked two LCDs, we confirmed that it was enough to make multi-layer images from three viewpoint images to display a 3Dimage. Limiting the number of viewpoint images, the viewing area that allows stereoscopic view becomes narrow. To broaden the viewing area, we track the head motion of the viewer and update screen images in real time so that the viewer can maintain correct stereoscopic view within +/- 20 degrees area. In addition, we render pseudo multiple viewpoint images using depth map, then we can generate motion parallax at the same time.

In order to provide a better quantitative and morphologic description of complex vascular lesions, we propose an approach of 3D reconstruction of the vessel internal wall, based on data fusion from two different imaging sources: two x ray digital angiography projections and a stack of endovascular echography slices. After extraction of echographic and angiographic information to be fused, a geometric model leads to the determination of the unknown parameters which allow the alignment of all data in a common reference frame. Both types of data are then directly included in a probabilistic reconstruction process based on Markov random fields. The Markovian model consists of cost functions reflecting x ray and ultrasonic data consistency and regularization elements to control the anatomic reality of the reconstruction. The optimal solution according to the definition criteria is obtained by minimizing the model energy with an algorithm based on simulated annealing. Preliminary results have been obtained with data acquired on a dog aorta. The accuracy of reconstruction by data fusion is significantly improved compared with results obtained with separate reconstruction from angiographic or echographic data. Taking into account all information available about the problem, the method avoids uncertainties and ambiguities of a reconstruction based only on one modality, and the probabilistic fusion solves the possible contradictions between both acquisitions.

Autostereoscopic 3Dimage overlay for augmented reality (AR) based surgical navigation has been studied and reported many times. For the purpose of surgical overlay, the 3Dimage is expected to have the same geometric shape as the original organ, and can be transformed to a specified location for image overlay. However, how to generate a 3Dimage with high geometric fidelity and quantitative evaluation of 3Dimage's geometric accuracy have not been addressed. This paper proposes a graphics processing unit (GPU) based computer-generated integral imaging pipeline for real-time autostereoscopic 3D display, and an automatic closed-loop 3Dimage calibration paradigm for displaying undistorted 3Dimages. Based on the proposed methods, a novel AR device for 3Dimage surgical overlay is presented, which mainly consists of a 3D display, an AR window, a stereo camera for 3D measurement, and a workstation for information processing. The evaluation on the 3Dimage rendering performance with 2560×1600 elemental image resolution shows the rendering speeds of 50-60 frames per second (fps) for surface models, and 5-8 fps for large medical volumes. The evaluation of the undistorted 3Dimage after the calibration yields sub-millimeter geometric accuracy. A phantom experiment simulating oral and maxillofacial surgery was also performed to evaluate the proposed AR overlay device in terms of the image registration accuracy, 3Dimage overlay accuracy, and the visual effects of the overlay. The experimental results show satisfactory image registration and image overlay accuracy, and confirm the system usability. PMID:25465067

Three-dimensional (3D) technology has become immensely popular in recent years and widely adopted in various applications. Hence, perceptual quality measurement of symmetrically and asymmetrically distorted 3Dimages has become an important, fundamental, and challenging issue in 3Dimaging research. In this paper, we propose a binocular-vision-based 3Dimage-quality measurement (IQM) metric. Consideration of the 3D perceptual properties of the primary visual cortex (V1) and the higher visual areas (V2) for 3D-IQM is the major technical contribution to this research. To be more specific, first, the metric simulates the receptive fields of complex cells (V1) using binocular energy response and binocular rivalry response and the higher visual areas (V2) using local binary patterns features. Then, three similarity scores of 3D perceptual properties between the reference and distorted 3Dimages are measured. Finally, by using support vector regression, three similarity scores are integrated into an overall 3D quality score. Experimental results for two public benchmark databases demonstrate that, in comparison with most current 2D and 3D metrics, the proposed metric achieves significantly higher consistency in alignment with subjective fidelity ratings. PMID:26367842

SAR range-Doppler images are inherently 2-dimensional. Targets with a height offset lay over onto offset range and azimuth locations. Just which image locations are laid upon depends on the imaging geometry, including depression angle, squint angle, and target bearing. This is the well known layover phenomenon. Images formed with different aperture geometries will exhibit different layover characteristics. These differences can be exploited to ascertain target height information, in a stereoscopic manner. Depending on the imaging geometries, height accuracy can be on the order of horizontal position accuracies, thereby rivaling the best IFSAR capabilities in fine resolution SAR images. All that is required for this to work are two distinct passes with suitably different geometries from any plain old SAR.

We present a pragmatic approach to image reconstruction for data from the micro crystal elements system (MiCES) fully 3D mouse imaging positron emission tomography (PET) scanner under construction at the University of Washington. Our approach is modelled on fully 3Dimage reconstruction used in clinical PET scanners, which is based on Fourier rebinning (FORE) followed by 2D iterative image reconstruction using ordered-subsets expectation-maximization (OSEM). The use of iterative methods allows modelling of physical effects (e.g., statistical noise, detector blurring, attenuation, etc), while FORE accelerates the reconstruction process by reducing the fully 3D data to a stacked set of independent 2D sinograms. Previous investigations have indicated that non-stationary detector point-spread response effects, which are typically ignored for clinical imaging, significantly impact image quality for the MiCES scanner geometry. To model the effect of non-stationary detector blurring (DB) in the FORE+OSEM(DB) algorithm, we have added a factorized system matrix to the ASPIRE reconstruction library. Initial results indicate that the proposed approach produces an improvement in resolution without an undue increase in noise and without a significant increase in the computational burden. The impact on task performance, however, remains to be evaluated.

We have developed a multi-view image integration system, which combines seven parallax video images into a single video image so that it fits the parallax barrier. The apertures of this barrier are not stripes but tiny rectangles that are arranged in the shape of stairs. Commodity hardware is used to satisfy a specification which requires that the resolution of each parallax video image is SXGA(1645×800 pixel resolution), the resulting integrated image is QUXGA-W(3840×2400 pixel resolution), and the frame rate is fifteen frames per second. The point is that the system can provide with QUXGA-W video image, which corresponds to 27MB, at 15fps, that is about 2Gbps. Using the integration system and a Liquid Crystal Display with the parallax barrier, we can enjoy an immersive live video image which supports seven viewpoints without special glasses. In addition, since the system can superimpose the CG images of the relevant seven viewpoints into the live video images, it is possible to communicate with remote users by sharing a virtual object.

We address the automatic detection of Ambush weapons such as rocket propelled grenades (RPGs) from range data which might be derived from multiple camera stereo with textured illumination or by other means. We describe our initial work in a new project involving the efficient acquisition of 3D scene data as well as discrete point invariant techniques to perform real time search for threats to a convoy. The shapes of the jump boundaries in the scene are exploited in this paper, rather than on-surface points, due to the large error typical of depth measurement at long range and the relatively high resolution obtainable in the transverse direction. We describe examples of the generation of a novel range-scaled chain code for detecting and matching jump boundaries.

Integral photography (IP) or integral imaging is a way to create natural-looking three-dimensional (3-D) images with full parallax. Integral three-dimensional television (integral 3-D TV) uses a method that electronically presents 3-Dimages in real time based on this IP method. The key component is a lens array comprising many micro-lenses for shooting and displaying. We have developed a prototype device with about 18,000 lenses using a super-high-definition camera with 2,000 scanning lines. Positional errors of these high-precision lenses as well as the camera's lenses will cause distortions in the elemental image, which directly affect the quality of the 3-Dimage and the viewing area. We have devised a way to compensate for such geometrical position errors and used it for the integral 3-D TV prototype, resulting in an improvement in both viewing zone and picture quality.

Registration of a pre operative plan with the intra operative position of the patient is still a largely unsolved problem. Current techniques generally require fiducials, either artificial or anatomic, to achieve the registration solution. Invariably these fiducials require implantation and/or direct digitisation. The technique described in this paper requires no digitisation or implantation of fiducials, but instead relies on the shape and form of the anatomy through a fully automated image comparison process. A pseudo image, generated from a virtual image intensifier's view of a CT dataset, is intra operatively compared with a real x-ray image. The principle is to align the virtual with the real image intensifier. The technique is an extension to the work undertaken by Domergue [1] and based on original ideas by Weese [4]. PMID:11317805

Real-time three-dimensional echocardiography (RT3DE) is a non-invasive method to visualize the heart. Disadvantageously, it suffers from non-uniform image quality and a limited field of view. Image quality can be improved by fusion of multiple echocardiography images. Successful registration of the images is essential for prosperous fusion. Therefore, this study examines the performance of different methods for intrasubject registration of multi-view apical RT3DE images. A total of 14 data sets was annotated by two observers who indicated the position of the apex and four points on the mitral valve ring. These annotations were used to evaluate registration. Multi-view end-diastolic (ED) as well as end-systolic (ES) images were rigidly registered in a multi-resolution strategy. The performance of single-frame and multi-frame registration was examined. Multi-frame registration optimizes the metric for several time frames simultaneously. Furthermore, the suitability of mutual information (MI) as similarity measure was compared to normalized cross-correlation (NCC). For initialization of the registration, a transformation that describes the probe movement was obtained by manually registering five representative data sets. It was found that multi-frame registration can improve registration results with respect to single-frame registration. Additionally, NCC outperformed MI as similarity measure. If NCC was optimized in a multi-frame registration strategy including ED and ES time frames, the performance of the automatic method was comparable to that of manual registration. In conclusion, automatic registration of RT3DE images performs as good as manual registration. As registration precedes image fusion, this method can contribute to improved quality of echocardiography images.

One of the less effective processes within current Computer Assisted Surgery systems, utilizing pre-operative planning, is the registration of the plan with the intra-operative position of the patient. The technique described in this paper requires no digitisation of anatomical features or fiducial markers but instead relies on image matching between pseudo and real x-ray images generated by a virtual and a real image intensifier respectively. The technique is an extension to the work undertaken by Weese [1]. PMID:10977585

ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

Recently, the computer generated hologram (CGH) calculated from real existing objects is more actively investigated to support holographic video and TV applications. In this paper, we propose a method of generating a hologram of the natural 3-D scene from multi-view images in order to provide motion parallax viewing with a suitable navigation range. After a unified 3-D point source set describing the captured 3-D scene is obtained from multi-view images, a hologram pattern supporting motion-parallax is calculated from the set using a point-based CGH method. We confirmed that 3-D scenes are faithfully reconstructed using numerical reconstruction.

The work here described regards multi-viewer auto- stereoscopic visualization of 3D models of anatomical structures and organs of the human body. High-quality 3D models of more than 1600 anatomical structures have been reconstructed using the Visualization Toolkit, a freely available C++ class library for 3D graphics and visualization. 2D images used for 3D reconstruction comes from the Visible Human Data Set. Auto-stereoscopic 3Dimage visualization is obtained using a prototype monitor developed at Philips Research Labs, UK. This special multiview 3D-LCD screen has been connected directly to a SGI workstation, where 3D reconstruction and medical imaging applications are executed. Dedicated software has been developed to implement multiview capability. A number of static or animated contemporary views of the same object can simultaneously be seen on the 3D-LCD screen by several observers, having a real 3D perception of the visualized scene without the use of extra media as dedicated glasses or head-mounted displays. Developed software applications allow real-time interaction with visualized 3D models, didactical animations and movies have been realized as well.

Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s‑1. However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time.

Magnetic particle imaging is a quantitative functional imaging technique that allows imaging of the spatial distribution of super-paramagnetic iron oxide particles at high temporal resolution. The raw data acquisition can be performed at frame rates of more than 40 volumes s(-1). However, to date image reconstruction is performed in an offline step and thus no direct feedback is available during the experiment. Considering potential interventional applications such direct feedback would be mandatory. In this work, an online reconstruction framework is implemented that allows direct visualization of the particle distribution on the screen of the acquisition computer with a latency of about 2 s. The reconstruction process is adaptive and performs block-averaging in order to optimize the signal quality for a given amount of reconstruction time. PMID:27182668

The dependence on macro-optical imaging of the human body in the assessment of possible disease is rapidly increasing concurrent with, and as a direct result of, advancements made in medical imaging technologies. Assessing the pulmonary airways through bronchoscopy is performed extensively in clinical practice however remains highly subjective due to limited visualization techniques and the lack of quantitative analyses. The representation of 3D structures in 2D visualization modes, although providing an insight to the structural content of the scene, may in fact skew the perception of the structural form. We have developed two methods for visualizing the optically derived airway mucosal features whilst preserving the structural scene integrity. Shape from shading (SFS) techniques can be used to extract 3D structural information from 2D optical images. The SFS technique presented addresses many limitations previously encountered in conventional techniques resulting in high-resolution 3D color images. The second method presented to combine both color and structural information relies on combined CT and bronchoscopy imaging modalities. External imaging techniques such as CT provide a means of determining the gross structural anatomy of the pulmonary airways, however lack the important optically derived mucosal color. Virtual bronchoscopy is used to provide a direct link between the CT derived structural anatomy and the macro-optically derived mucosal color. Through utilization of a virtual and true bronchoscopy matching technique we are able to directly extract combined structurally sound 3D color segments of the pulmonary airways. Various pulmonary airway diseases are assessed and the resulting combined color and texture results are presented demonstrating the effectiveness of the presented techniques.

Biological specimens are three-dimensional structures. However, when capturing their images through a microscope, there is only one plane in the field of view that is in focus, and out-of-focus portions of the specimen affect image quality in the in-focus plane. It is well-established that the microscope"s point spread function (PSF) can be used for blur quantitation, for the restoration of real images. However, this is an ill-posed problem, with no unique solution and with high computational complexity. In this work, instead of estimating and using the PSF, we studied focus quantitation in multi-spectral image sets. A gradient map we designed was used to evaluate the sharpness degree of each pixel, in order to identify blurred areas not to be considered. Experiments with realistic multi-spectral Pap smear images showed that measurement of their sharp gradients can provide depth information roughly comparable to human perception (through a microscope), while avoiding PSF estimation. Spectrum and morphometrics-based statistical analysis for abnormal cell detection can then be implemented in an image database where the axial structure has been refined.

Utilization of an acoustic camera for range measurements is a key advantage for 3-D shape recovery of underwater targets by opti-acoustic stereo imaging, where the associated epipolar geometry of optical and acoustic image correspondences can be described in terms of conic sections. In this paper, we propose methods for system calibration and 3-D scene reconstruction by maximum likelihood estimation from noisy image measurements. The recursive 3-D reconstruction method utilized as initial condition a closed-form solution that integrates the advantages of two other closed-form solutions, referred to as the range and azimuth solutions. Synthetic data tests are given to provide insight into the merits of the new target imaging and 3-D reconstruction paradigm, while experiments with real data confirm the findings based on computer simulations, and demonstrate the merits of this novel 3-D reconstruction paradigm. PMID:19380272

This paper explores three-dimensional (3D) interferometric synthetic aperture radar (IFSAR) image reconstruction when multiple scattering centers and noise are present in a radar resolution cell. We introduce an IFSAR scattering model that accounts for both multiple scattering centers and noise. The problem of 3Dimage reconstruction is then posed as a multiple hypothesis detection and estimation problem; resolution cells containing a single scattering center are detected and the 3D location of these cells' pixels are estimated; all other pixels are rejected from the image. Detection and estimation statistics are derived using the multiple scattering center IFSAR model. A 3Dimage reconstruction algorithm using these statistics is then presented, and its performance is evaluated for a 3D reconstruction of a backhoe from noisy IFSAR data.

In this paper, the establishment of a remote laboratory for phase-aided 3D microscopic imaging and metrology is presented. Proposed remote laboratory consists of three major components, including the network-based infrastructure for remote control and data management, the identity verification scheme for user authentication and management, and the local experimental system for phase-aided 3D microscopic imaging and metrology. The virtual network computer (VNC) is introduced to remotely control the 3D microscopic imaging system. Data storage and management are handled through the open source project eSciDoc. Considering the security of remote laboratory, the fingerprint is used for authentication with an optical joint transform correlation (JTC) system. The phase-aided fringe projection 3D microscope (FP-3DM), which can be remotely controlled, is employed to achieve the 3Dimaging and metrology of micro objects.

The development of three dimensional (3D) cell cultures represents a big step for the better understanding of cell behavior and disease in a more natural like environment, providing not only single but multiple cell type interactions in a complex 3D matrix, highly resembling physiological conditions. Light sheet fluorescence microscopy (LSFM) is becoming an excellent tool for fast imaging of such 3D biological structures. We demonstrate the potential of this technique for the imaging of human differentiated 3D neural aggregates in fixed and live samples, namely calcium imaging and cell death processes, showing the power of imaging modality compared with traditional microscopy. The combination of light sheet microscopy and 3D neural cultures will open the door to more challenging experiments involving drug testing at large scale as well as a better understanding of relevant biological processes in a more realistic environment. PMID:25161607

This paper presents a compressed sensing based reconstruction method for 3D digital breast tomosynthesis (DBT) imaging. Algebraic reconstruction technique (ART) has been in use in DBT imaging by minimizing the isotropic total variation (TV) of the reconstructed image. The resolution in DBT differs in sagittal and axial directions which should be encountered during the TV minimization. In this study we develop a 3D anisotropic TV (ATV) minimization by considering the different resolutions in different directions. A customized 3D Shepp-logan phantom was generated to mimic a real DBT image by considering the overlapping tissue and directional resolution issues. Results of the ART, ART+3D TV and ART+3D ATV are compared using structural similarity (SSIM) diagram. PMID:25571377

The O-arm is a cone beam imaging system designed primarily to support orthopedic surgery and is also used for image-guided and vascular surgery. Using a gantry that can be opened or closed, the O-arm can function as a 2-dimensional (2D) fluoroscopy device or collect 3-dimensional (3D) volumetric imaging data like a CT system. Clinical applications of the O-arm in spine surgical procedures, assessment of pedicle screw position, and kyphoplasty procedures show that the O-arm 3D mode provides enhanced imaging information compared to radiographs or fluoroscopy alone. In this study, the image quality of an O-arm system was quantitatively evaluated. A 20 cm diameter CATPHAN 424 phantom was scanned using the pre-programmed head protocols: small/medium (120 kVp, 100 mAs), large (120 kVp, 128 mAs), and extra-large (120 kVp, 160 mAs) in 3D mode. High resolution reconstruction mode (512×512×0.83 mm) was used to reconstruct images for the analysis of low and high contrast resolution, and noise power spectrum. MTF was measured using the point spread function. The results show that the O-arm image is uniform but with a noise pattern which cannot be removed by simply increasing the mAs. The high contrast resolution of the O-arm system was approximately 9 lp/cm. The system has a 10% MTF at 0.45 mm. The low-contrast resolution cannot be decided due to the noise pattern. For surgery where locations of a structure are emphasized over a survey of all image details, the image quality of the O-arm is well accepted clinically.

Endovascular image-guided interventions (EIGI) involve navigation of a catheter through the vasculature followed by application of treatment at the site of anomaly using live 2D projection images for guidance. 3Dimages acquired prior to EIGI are used to quantify the vascular anomaly and plan the intervention. If fused with the information of live 2D images they can also facilitate navigation and treatment. For this purpose 3D-2D image registration is required. Although several 3D-2D registration methods for EIGI achieve registration accuracy below 1 mm, their clinical application is still limited by insufficient robustness or reliability. In this paper, we propose a 3D-2D registration method based on matching a 3D vasculature model to intensity gradients of live 2D images. To objectively validate 3D-2D registration methods, we acquired a clinical image database of 10 patients undergoing cerebral EIGI and established "gold standard" registrations by aligning fiducial markers in 3D and 2D images. The proposed method had mean registration accuracy below 0.65 mm, which was comparable to tested state-of-the-art methods, and execution time below 1 s. With the highest rate of successful registrations and the highest capture range the proposed method was the most robust and thus a good candidate for application in EIGI. PMID:23649179

This is a three-dimensional view of Isabela, one of the Galapagos Islands located off the western coast of Ecuador, South America. This view was constructed by overlaying a Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) image on a digital elevation map produced by TOPSAR, a prototype airborne interferometric radar which produces simultaneous image and elevation data. The vertical scale in this image is exaggerated by a factor of 1.87. The SIR-C/X-SAR image was taken on the 40th orbit of space shuttle Endeavour. The image is centered at about 0.5 degree south latitude and 91 degrees west longitude and covers an area of 75 by 60 kilometers (47 by 37 miles). The radar incidence angle at the center of the image is about 20 degrees. The western Galapagos Islands, which lie about 1,200 kilometers (750 miles)west of Ecuador in the eastern Pacific, have six active volcanoes similar to the volcanoes found in Hawaii and reflect the volcanic processes that occur where the ocean floor is created. Since the time of Charles Darwin's visit to the area in 1835, there have been more than 60 recorded eruptions on these volcanoes. This SIR-C/X-SAR image of Alcedo and Sierra Negra volcanoes shows the rougher lava flows as bright features, while ash deposits and smooth pahoehoe lava flows appear dark. Vertical exaggeration of relief is a common tool scientists use to detect relationships between structure (for example, faults, and fractures) and topography. Spaceborne Imaging Radar-C and X-Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data

We have shown that multiple spheres can be imaged by linear and planar EM arrays using only one component of polarization. The imaging approach involves calculating the SVD of the scattering response matrix, selecting a subset of singular values that represents noise, and evaluating the MUSIC functional. The noise threshold applied to the spectrum of singular values for optimal performance is typically around 1%. The resulting signal subspace includes more than one singular value per sphere. The presence of reflections from the ground improves height localization, even for a linear array parallel to the ground. However, the interference between direct and reflected energy modulates the field, creating periodic nulls that can obscure targets in typical images. These nulls are largely eliminated by normalizing the MUSIC functional with the broadside beam pattern of the array. The resulting images show excellent localization for 1 and 2 spheres. The performance for the 3 sphere configurations are complicated by shadowing effects and the greater range of the 3rd sphere in case 2. Two of the three spheres are easily located by MUSIC but the third is difficult to distinguish from other local maxima of the complex imaging functional. Improvement is seen when the linear array is replace with a planar array, which increases the effective aperture height. Further analysis of the singular values and their relationship to modes of scattering from the spheres, as well as better ways to exploit polarization, should improve performance. Work along these lines is currently being pursued by the authors.

Recently, 3D displays and videos have generated a lot of interest in the consumer electronics industry. To make 3D capture and playback popular and practical, a user friendly playback interface is desirable. Towards this end, we built a real time software 3D video player. The 3D video player displays user captured 3D videos, provides for various 3D specific image processing functions and ensures a pleasant viewing experience. Moreover, the player enables user interactivity by providing digital zoom and pan functionalities. This real time 3D player was implemented on the GPU using CUDA and OpenGL. The player provides user interactive 3D video playback. Stereo images are first read by the player from a fast drive and rectified. Further processing of the images determines the optimal convergence point in the 3D scene to reduce eye strain. The rationale for this convergence point selection takes into account scene depth and display geometry. The first step in this processing chain is identifying keypoints by detecting vertical edges within the left image. Regions surrounding reliable keypoints are then located on the right image through the use of block matching. The difference in the positions between the corresponding regions in the left and right images are then used to calculate disparity. The extrema of the disparity histogram gives the scene disparity range. The left and right images are shifted based upon the calculated range, in order to place the desired region of the 3D scene at convergence. All the above computations are performed on one CPU thread which calls CUDA functions. Image upsampling and shifting is performed in response to user zoom and pan. The player also consists of a CPU display thread, which uses OpenGL rendering (quad buffers). This also gathers user input for digital zoom and pan and sends them to the processing thread.

In Thailand, there are several types of (tangible) cultural heritages. This work focuses on 3D modeling of the heritage objects from multi-views images. The images are acquired by using a DSLR camera which costs around 1,500 (camera and lens). Comparing with a 3D laser scanner, the camera is cheaper and lighter than the 3D scanner. Hence, the camera is available for public users and convenient for accessing narrow areas. The acquired images consist of various sculptures and architectures in Wat-Pho which is a Buddhist temple located behind the Grand Palace (Bangkok, Thailand). Wat-Pho is known as temple of the reclining Buddha and the birthplace of traditional Thai massage. To compute the 3D models, a diagram is separated into following steps; Data acquisition, Image matching, Image calibration and orientation, Dense matching and Point cloud processing. For the initial work, small heritages less than 3 meters height are considered for the experimental results. A set of multi-views images of an interested object is used as input data for 3D modeling. In our experiments, 3D models are obtained from MICMAC (open source) software developed by IGN, France. The output of 3D models will be represented by using standard formats of 3D point clouds and triangulated surfaces such as .ply, .off, .obj, etc. To compute for the efficient 3D models, post-processing techniques are required for the final results e.g. noise reduction, surface simplification and reconstruction. The reconstructed 3D models can be provided for public access such as website, DVD, printed materials. The high accurate 3D models can also be used as reference data of the heritage objects that must be restored due to deterioration of a lifetime, natural disasters, etc.

A three-dimensional capacitance density imaging of a gasified bed or the like in a containment vessel is achieved using a plurality of electrodes provided circumferentially about the bed in levels and along the bed in channels. The electrodes are individually and selectively excited electrically at each level to produce a plurality of current flux field patterns generated in the bed at each level. The current flux field patterns are suitably sensed and a density pattern of the bed at each level determined. By combining the determined density patterns at each level, a three-dimensional density image of the bed is achieved.

Nowadays, with the development of the urban areas, the automatic reconstruction of the buildings, as an important objects of the city complex structures, became a challenging topic in computer vision and photogrammetric researches. In this paper, the capability of multi-view Unmanned Aerial Vehicles (UAVs) images is examined to provide a 3D model of complex building façades using an efficient image-based modelling workflow. The main steps of this work include: pose estimation, point cloud generation, and 3D modelling. After improving the initial values of interior and exterior parameters at first step, an efficient image matching technique such as Semi Global Matching (SGM) is applied on UAV images and a dense point cloud is generated. Then, a mesh model of points is calculated using Delaunay 2.5D triangulation and refined to obtain an accurate model of building. Finally, a texture is assigned to mesh in order to create a realistic 3D model. The resulting model has provided enough details of building based on visual assessment.

The ability to create 3D models, using registered texel images (fused ladar and digital imagery), is an important topic in remote sensing. These models are automatically generated by matching multiple texel images into a single common reference frame. However, rendering a sequence of independently registered texel images often provides challenges. Although accurately registered, the model textures are often incorrectly overlapped and interwoven when using standard rendering techniques. Consequently, corrections must be done after all the primitives have been rendered, by determining the best texture for any viewable fragment in the model. Determining the best texture is difficult, as each texel image remains independent after registration. The depth data is not merged to form a single 3D mesh, thus eliminating the possibility of generating a fused texture atlas. It is therefore necessary to determine which textures are overlapping and how to best combine them dynamically during the render process. The best texture for a particular pixel can be defined using 3D geometric criteria, in conjunction with a real-time, view-dependent ranking algorithm. As a result, overlapping texture fragments can now be hidden, exposed, or blended according to their computed measure of reliability.

This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach. PMID:22346575

This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach. PMID:22346575

Accurate metrology of the anterior chamber of the eye is useful for a number of diagnostic and clinical applications. In particular, accurate corneal topography and corneal thickness data is desirable for fitting contact lenses, screening for diseases and monitoring corneal changes. Anterior OCT systems can be used to measure anterior chamber surfaces, however accurate curvature measurements for single point scanning systems are known to be very sensitive to patient movement. To overcome this problem we have developed a parallel 3D spectral metrology system that captures simultaneous A-scans on a 2D lateral grid. This approach enables estimates of the elevation and curvature of anterior and posterior corneal surfaces that are robust to sample movement. Furthermore, multiple simultaneous surface measurements greatly improve the ability to register consecutive frames and enable aggregate measurements over a finer lateral grid. A key element of our approach has been to exploit standard low cost optical components including lenslet arrays and a 2D sensor to provide a path towards low cost implementation. We demonstrate first prototypes based on 6 Mpixel sensor using a 250 μm pitch lenslet array with 300 sample beams to achieve an RMS elevation accuracy of 1μm with 95 dB sensitivity and a 7.0 mm range. Initial tests on Porcine eyes, model eyes and calibration spheres demonstrate the validity of the concept. With the next iteration of designs we expect to be able to achieve over 1000 simultaneous A-scans in excess of 75 frames per second.

This is a three-dimensional perspective view of a false-color image of the eastern part of the Big Island of Hawaii. It was produced using all three radar frequencies -- X-band, C-band and L-band -- from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying on the space shuttle Endeavour, overlaid on a U.S. Geological Survey digital elevation map. Visible in the center of the image in blue are the summit crater (Kilauea Caldera) which contains the smaller Halemaumau Crater, and the line of collapse craters below them that form the Chain of Craters Road. The image was acquired on April 12, 1994 during orbit 52 of the space shuttle. The area shown is approximately 34 by 57 kilometers (21 by 35 miles) with the top of the image pointing toward northwest. The image is centered at about 155.25 degrees west longitude and 19.5 degrees north latitude. The false colors are created by displaying three radar channels of different frequency. Red areas correspond to high backscatter at L-HV polarization, while green areas exhibit high backscatter at C-HV polarization. Finally, blue shows high return at X-VV polarization. Using this color scheme, the rain forest appears bright on the image, while the green areas correspond to lower vegetation. The lava flows have different colors depending on their types and are easily recognizable due to their shapes. The flows at the top of the image originated from the Mauna Loa volcano. Kilauea volcano has been almost continuously active for more than the last 11 years. Field teams that were on the ground specifically to support these radar observations report that there was vigorous surface activity about 400 meters (one-quartermile) inland from the coast. A moving lava flow about 200 meters (650 feet) in length was observed at the time of the shuttle overflight, raising the possibility that subsequent images taken during this mission will show changes in the landscape. Currently, most of the lava that is

This is a three-dimensional perspective view of a false-color image of the eastern part of the Big Island of Hawaii. It was produced using all three radar frequencies -- X-band, C-band and L-band -- from the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) flying on the space shuttle Endeavour, overlaid on a U.S. Geological Survey digital elevation map. Visible in the center of the image in blue are the summit crater (Kilauea Caldera) which contains the smaller Halemaumau Crater, and the line of collapse craters below them that form the Chain of Craters Road. The image was acquired on April 12, 1994 during orbit 52 of the space shuttle. The area shown is approximately 34 by 57 kilometers (21 by 35 miles) with the top of the image pointing toward northwest. The image is centered at about 155.25 degrees west longitude and 19.5 degrees north latitude. The false colors are created by displaying three radar channels of different frequency. Red areas correspond to high backscatter at L-HV polarization, while green areas exhibit high backscatter at C-HV polarization. Finally, blue shows high return at X-VV polarization. Using this color scheme, the rain forest appears bright on the image, while the green areas correspond to lower vegetation. The lava flows have different colors depending on their types and are easily recognizable due to their shapes. The flows at the top of the image originated from the Mauna Loa volcano. Kilauea volcano has been almost continuously active for more than the last 11 years. Field teams that were on the ground specifically to support these radar observations report that there was vigorous surface activity about 400 meters (one-quartermile) inland from the coast. A moving lava flow about 200 meters (650 feet) in length was observed at the time of the shuttle overflight, raising the possibility that subsequent images taken during this mission will show changes in the landscape. Currently, most of the lava that is

Inactivation of the retinoblastoma gene in mouse embryos causes tissue infiltrations into critical sections of the placenta, which has been shown to affect fetal survivability. Our collaborators in cancer genetics are extremely interested in examining the three dimensional nature of these infiltrations given a stack of two dimensional light microscopy images. Three sets of wildtype and mutant placentas was sectioned serially and digitized using a commercial light microscopy scanner. Each individual placenta dataset consisted of approximately 1000 images totaling 700 GB in size, which were registered into a volumetric dataset using National Library of Medicine's (NIH/NLM) Insight Segmentation and Registration Toolkit (ITK). This paper describes our method for image registration to aid in volume visualization of tissue level intermixing for both wildtype and Rb - specimens. The registration process faces many challenges arising from the large image sizes, damages during sectioning, staining gradients both within and across sections, and background noise. These issues limit the direct application of standard registration techniques due to frequent convergence to local solutions. In this work, we develop a mixture of automated and semi-automated enhancements with ground-truth validation for the mutual information-based registration algorithm. Our final volume renderings clearly show tissue intermixing differences between both wildtype and Rb - specimens which are not obvious prior to registration.

A method of determining three-dimensional motion and structure from two image frames is presented. The method requires eight point correspondences between the two frames, from which motion and structure parameters are determined by solving a set of eight linear equations and a singular value decomposition of a 3x3 matrix. It is shown that the solution thus obtained is unique.

Image interpolation is an important operation that is widely used in medical imaging, image processing, and computer graphics. A variety of interpolation methods are available in the literature. However, their systematic evaluation is lacking. At a previous meeting, we presented a framework for the task independent comparison of interpolation methods based on a variety of medical image data pertaining to different parts of the human body taken from different modalities. In this new work, we present an objective, task-specific framework for evaluating interpolation techniques. The task considered is how the interpolation methods influence the accuracy of quantification of the total volume of lesions in the brain of Multiple Sclerosis (MS) patients. Sixty lesion detection experiments coming from ten patient studies, two subsampling techniques and the original data, and 3 interpolation methods is presented along with a statistical analysis of the results. This work comprises a systematic framework for the task-specific comparison of interpolation methods. Specifically, the influence of three interpolation methods in MS lesion quantification is compared.

A currently available 2-D high-resolution, optical molecular imaging system was modified by the addition of a structured illumination source, OptigridTM, to investigate the feasibility of providing depth resolution along the optical axis. The modification involved the insertion of the OptigridTM and a lens in the path between the light source and the image plane, as well as control and signal processing software. Projection of the OptigridTM onto the imaging surface at an angle, was resolved applying the Scheimpflug principle. The illumination system implements modulation of the light source and provides a framework for capturing depth resolved mages. The system is capable of in-focus projection of the OptigridTM at different spatial frequencies, and supports the use of different lenses. A calibration process was developed for the system to achieve consistent phase shifts of the OptigridTM. Post-processing extracted depth information using depth modulation analysis using a phantom block with fluorescent sheets at different depths. An important aspect of this effort was that it was carried out by a multidisciplinary team of engineering and science students as part of a capstone senior design program. The disciplines represented are mechanical engineering, electrical engineering and imaging science. The project was sponsored by a financial grant from New York State with equipment support from two industrial concerns. The students were provided with a basic imaging concept and charged with developing, implementing, testing and validating a feasible proof-of-concept prototype system that was returned to the originator of the concept for further evaluation and characterization.

We investigated cine-mode portal imaging on a Varian Trilogy accelerator and found that the linearity and other dosimetric properties are sufficient for 3D dose reconstruction as used in patient-specific quality assurance for VMAT (RapidArc) treatments. We also evaluated the gantry angle label in the portal image file header as a surrogate for the true imaged angle. The precision is only just adequate for the 3D evaluation method chosen, as discrepancies of 2° were observed.

3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing day to day for various engineering and non-engineering applications. Generally three main image based approaches are using for virtual 3D city models generation. In first approach, researchers used Sketch based modeling, second method is Procedural grammar based modeling and third approach is Close range photogrammetry based modeling. Literature study shows that till date, there is no complete solution available to create complete 3D city model by using images. These image based methods also have limitations This paper gives a new approach towards image based virtual 3D city modeling by using close range photogrammetry. This approach is divided into three sections. First, data acquisition process, second is 3D data processing, and third is data combination process. In data acquisition process, a multi-camera setup developed and used for video recording of an area. Image frames created from video data. Minimum required and suitable video image frame selected for 3D processing. In second section, based on close range photogrammetric principles and computer vision techniques, 3D model of area created. In third section, this 3D model exported to adding and merging of other pieces of large area. Scaling and alignment of 3D model was done. After applying the texturing and rendering on this model, a final photo-realistic textured 3D model created. This 3D model transferred into walk-through model or in movie form. Most of the processing steps are automatic. So this method is cost effective and less laborious. Accuracy of this model is good. For this research work, study area is the campus of department of civil engineering, Indian Institute of Technology, Roorkee. This campus acts as a prototype for city. Aerial photography is restricted in many country

This is a three-dimensional perspective view of Missoula, Montana, created by combining two spaceborne radar images using a technique known as interferometry. Visualizations like this are useful because they show scientists the shapes of the topographic features such as mountains and valleys. This technique helps to clarify the relationships of the different types of materials on the surface detected by the radar. The view is looking north-northeast. The blue circular area at the lower left corner is a bend of the Bitterroot River just before it joins the Clark Fork, which runs through the city. Crossing the Bitterroot River is the bridge of U.S. Highway 93. Highest mountains in this image are at elevations of 2,200 meters (7,200 feet). The city is about 975 meters (3,200 feet) above sea level. The bright yellow areas are urban and suburban zones, dark brown and blue-green areas are grasslands, bright green areas are farms, light brown and purple areas are scrub and forest, and bright white and blue areas are steep rocky slopes. The two radar images were taken on successive days by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) onboard the space shuttle Endeavour in October 1994. The digital elevation map was produced using radar interferometry, a process in which radar data are acquired on different passes of the space shuttle. The two data passes are compared to obtain elevation information. Radar image data are draped over the topography to provide the color with the following assignments: red is L-band vertically transmitted, vertically received; green is C-band vertically transmitted, vertically received; and blue are differences seen in the L-band data between the two days. This image is centered near 46.9 degrees north latitude and 114.1 degrees west longitude. No vertical exaggeration factor has been applied to the data. SIR-C/X-SAR, a joint mission of the German, Italian and United States space agencies, is part of NASA

This is a three-dimensional perspective view of Long Valley, California by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar on board the space shuttle Endeavour. This view was constructed by overlaying a color composite SIR-C image on a digital elevation map. The digital elevation map was produced using radar interferometry, a process by which radar data are acquired on different passes of the space shuttle and, which then, are compared to obtain elevation information. The data were acquired on April 13, 1994 and on October 3, 1994, during the first and second flights of the SIR-C/X-SAR radar instrument. The color composite radar image was produced by assigning red to the C-band (horizontally transmitted and vertically received) polarization; green to the C-band (vertically transmitted and received) polarization; and blue to the ratio of the two data sets. Blue areas in the image are smooth and yellow areas are rock outcrops with varying amounts of snow and vegetation. The view is looking north along the northeastern edge of the Long Valley caldera, a volcanic collapse feature created 750,000 years ago and the site of continued subsurface activity. Crowley Lake is off the image to the left. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are induced by human activity. SIR-C was developed by NASA's Jet Propulsion Laboratory

This three-dimensional perspective view of Long Valley, California was created from data taken by the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar on board the space shuttle Endeavour. This image was constructed by overlaying a color composite SIR-C radar image on a digital elevation map. The digital elevation map was produced using radar interferometry, a process by which radar data are acquired on different passes of the space shuttle. The two data passes are compared to obtain elevation information. The interferometry data were acquired on April 13,1994 and on October 3, 1994, during the first and second flights of the SIR-C/X-SAR instrument. The color composite radar image was taken in October and was produced by assigning red to the C-band (horizontally transmitted and vertically received) polarization; green to the C-band (vertically transmitted and received) polarization; and blue to the ratio of the two data sets. Blue areas in the image are smooth and yellow areas are rock outcrops with varying amounts of snow and vegetation. The view is looking north along the northeastern edge of the Long Valley caldera, a volcanic collapse feature created 750,000 years ago and the site of continued subsurface activity. Crowley Lake is the large dark feature in the foreground. Spaceborne Imaging Radar-C and X-band Synthetic Aperture Radar (SIR-C/X-SAR) is part of NASA's Mission to Planet Earth. The radars illuminate Earth with microwaves, allowing detailed observations at any time, regardless of weather or sunlight conditions. SIR-C/X-SAR uses three microwave wavelengths: L-band (24 cm), C-band (6 cm) and X-band (3 cm). The multi-frequency data will be used by the international scientific community to better understand the global environment and how it is changing. The SIR-C/X-SAR data, complemented by aircraft and ground studies, will give scientists clearer insights into those environmental changes which are caused by nature and those changes which are

This three-dimensional perspective of the remote Karakax Valley in the northern Tibetan Plateau of western China was created by combining two spaceborne radar images using a technique known as interferometry. Visualizations like this are helpful to scientists because they reveal where the slopes of the valley are cut by erosion, as well as the accumulations of gravel deposits at the base of the mountains. These gravel deposits, called alluvial fans, are a common landform in desert regions that scientists are mapping in order to learn more about Earth's past climate changes. Higher up the valley side is a clear break in the slope, running straight, just below the ridge line. This is the trace of the Altyn Tagh fault, which is much longer than California's San Andreas fault. Geophysicists are studying this fault for clues it may be able to give them about large faults. Elevations range from 4000 m (13,100 ft) in the valley to over 6000 m (19,700 ft) at the peaks of the glaciated Kun Lun mountains running from the front right towards the back. Scale varies in this perspective view, but the area is about 20 km (12 miles) wide in the middle of the image, and there is no vertical exaggeration. The two radar images were acquired on separate days during the second flight of the Spaceborne Imaging Radar-C/X-band Synthetic Aperture Radar (SIR-C/X-SAR) aboard the space shuttle Endeavour in October 1994. The interferometry technique provides elevation measurements of all points in the scene. The resulting digital topographic map was used to create this view, looking northwest from high over the valley. Variations in the colors can be related to gravel, sand and rock outcrops. This image is centered at 36.1 degrees north latitude, 79.2 degrees east longitude. Radar image data are draped over the topography to provide the color with the following assignments: Red is L-band vertically transmitted, vertically received; green is the average of L-band vertically transmitted

In this paper, we introduce a novel and efficient algorithm for reconstructing the 3D locations of tumor sites from a set of 2D bioluminescence images which are taken by a same camera but after continually rotating the object by a small angle. Our approach requires a much simpler set up than those using multiple cameras, and the algorithmic steps in our framework are efficient and robust enough to facilitate its use in analyzing the repeated imaging of a same animal transplanted with gene marked cells. In order to visualize in 3D the structure of the tumor, we also co-register the BLI-reconstructed crude structure with detailed anatomical structure extracted from high-resolution microCT on a single platform. We present our method using both phantom studies and real studies on small animals.

In the field of fluid mechanics, the resolution of computational schemes has outpaced experimental methods and widened the gap between predicted and observed phenomena in fluid flows. Thus, a need exists for an accessible method capable of resolving three-dimensional (3D) data sets for a range of problems. We present a novel technique for performing quantitative 3Dimaging of many types of flow fields. The 3D technique enables investigation of complicated velocity fields and bubbly flows. Measurements of these types present a variety of challenges to the instrument. For instance, optically dense bubbly multiphase flows cannot be readily imaged by traditional, non-invasive flow measurement techniques due to the bubbles occluding optical access to the interior regions of the volume of interest. By using Light Field Imaging we are able to reparameterize images captured by an array of cameras to reconstruct a 3D volumetric map for every time instance, despite partial occlusions in the volume. The technique makes use of an algorithm known as synthetic aperture (SA) refocusing, whereby a 3D focal stack is generated by combining images from several cameras post-capture 1. Light Field Imaging allows for the capture of angular as well as spatial information about the light rays, and hence enables 3D scene reconstruction. Quantitative information can then be extracted from the 3D reconstructions using a variety of processing algorithms. In particular, we have developed measurement methods based on Light Field Imaging for performing 3D particle image velocimetry (PIV), extracting bubbles in a 3D field and tracking the boundary of a flickering flame. We present the fundamentals of the Light Field Imaging methodology in the context of our setup for performing 3DPIV of the airflow passing over a set of synthetic vocal folds, and show representative results from application of the technique to a bubble-entraining plunging jet. PMID:23486112

A snapshot 3-Dimensional Optical Coherence Tomography system was developed using Image MappingSpectrometry. This system can give depth information (Z) at different spatial positions (XY) withinone camera integration time to potentially reduce motion artifact and enhance throughput. Thecurrent (x,y,λ) datacube of (85×356×117) provides a 3Dvisualization of sample with 400 μm depth and 13.4μm in transverse resolution. Axial resolution of 16.0μm can also be achieved in this proof-of-concept system. We present ananalysis of the theoretical constraints which will guide development of future systems withincreased imaging depth and improved axial and lateral resolutions. PMID:23736629

The capability to extract objective and quantitatively accurate information from 3-D radiographic biomedical images has not kept pace with the capabilities to produce the images themselves. This is rather an ironic paradox, since on the one hand the new 3-D and 4-D imaging capabilities promise significant potential for providing greater specificity and sensitivity (i.e., precise objective discrimination and accurate quantitative measurement of body tissue characteristics and function) in clinical diagnostic and basic investigative imaging procedures than ever possible before, but on the other hand, the momentous advances in computer and associated electronic imaging technology which have made these 3-Dimaging capabilities possible have not been concomitantly developed for full exploitation of these capabilities. Therefore, we have developed a powerful new microcomputer-based system which permits detailed investigations and evaluation of 3-D and 4-D (dynamic 3-D) biomedical images. The system comprises a special workstation to which all the information in a large 3-Dimage data base is accessible for rapid display, manipulation, and measurement. The system provides important capabilities for simultaneously representing and analyzing both structural and functional data and their relationships in various organs of the body. This paper provides a detailed description of this system, as well as some of the rationale, background, theoretical concepts, and practical considerations related to system implementation. ImagesFigure 5Figure 7Figure 8Figure 9Figure 10Figure 11Figure 12Figure 13Figure 14Figure 15Figure 16

Currently, one major research field in radiotheraphy is focused on patient setup verification and on detection of organ motion and deformation. A phantom study is performed to demonstrate the feasibility of image guidance in radiotherapy. Patient setup errors are simulated with a humanoid phantom, which is imaged using a linear accelerator and a therapy simulator to address megavoltage and kilovoltage (kV) computed tomography (CT), respectively. Projections are recorded by a flat panel imager. The various data sets of the humanoid phantom are compared by mutual information matching. The CT investigations show that the spatial resolution is better than 1.6 mm for high contrast objects. The uncertainties remaining after mutual information matching are found to be less than 1 mm for translations and 1 degree(s) for rotations. The phantom study indicates that the detection of patient setup errors as well as organ motion or deformation is possible with a high accuracy, especially if a kV X-ray tube could be attached to the linear accelerator. The presented method allows sophisticated quality assurance of beam delivery in each fraction and may even enable the use of new concepts of adaptive radiotherapy.

A new method for stenosis quantification from 3D X-ray angiography images has been evaluated on both phantom and clinical data. On phantoms, for the parts larger or equal to 3 mm, the standard deviation of the measurement error has always found to be less or equal to 0.4 mm, and the maximum measurement error less than 0.17 mm. No clear relationship has been observed between the performances of the quantification method and the acquisition FoV. On clinical data, the 3D quantification method proved to be more robust to vessel bifurcations than its 3D equivalent. On a total of 15 clinical cases, the differences between 2D and 3D quantification were always less than 0.7 mm. The conclusion is that stenosis quantification from 3D X-4ay angiography images is an attractive alternative to quantification from 2D X-ray images.

We have developed a 3D super-resolution microscopy method that enables deep imaging in cells. This technique relies on the effective combination of multifocus microscopy and astigmatic 3D single-molecule localization microscopy. We describe the optical system and the fabrication process of its key element, the multifocus grating. Then, two strategies for localizing emitters with our imaging method are presented and compared with a previously described deep 3D localization algorithm. Finally, we demonstrate the performance of the method by imaging the nuclear envelope of eukaryotic cells reaching a depth of field of ~4µm. PMID:27375935

Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.

Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion candidates. Applying the algorithm to 100 thoracic 3-D CT images and then by follow-up 3-D CT images, we demonstrate its potential effectiveness to assist radiologists and physicians to quantitatively evaluate the emphysematous lesions distribution and their evolution in time interval changes.

We have developed a 3D super-resolution microscopy method that enables deep imaging in cells. This technique relies on the effective combination of multifocus microscopy and astigmatic 3D single-molecule localization microscopy. We describe the optical system and the fabrication process of its key element, the multifocus grating. Then, two strategies for localizing emitters with our imaging method are presented and compared with a previously described deep 3D localization algorithm. Finally, we demonstrate the performance of the method by imaging the nuclear envelope of eukaryotic cells reaching a depth of field of ~4µm. PMID:27375935

3D face modeling has been one of the greatest challenges for researchers in computer graphics for many years. Various methods have been used to model the shape and texture of faces under varying illumination and pose conditions from a single given image. In this paper, we propose a novel method for the 3D face synthesis and reconstruction by using a simple and efficient global optimizer. A 3D-2D matching algorithm which employs the integration of the 3D morphable model (3DMM) and the differential evolution (DE) algorithm is addressed. In 3DMM, the estimation process of fitting shape and texture information into 2D images is considered as the problem of searching for the global minimum in a high dimensional feature space, in which optimization is apt to have local convergence. Unlike the traditional scheme used in 3DMM, DE appears to be robust against stagnation in local minima and sensitiveness to initial values in face reconstruction. Benefitting from DE's successful performance, 3D face models can be created based on a single 2D image with respect to various illuminating and pose contexts. Preliminary results demonstrate that we are able to automatically create a virtual 3D face from a single 2D image with high performance. The validation process shows that there is only an insignificant difference between the input image and the 2D face image projected by the 3D model.

Three-dimensional (3D) high resolution microscopic images have high potential for improving the understanding of both normal and disease processes where structural changes or spatial relationship of disease features are significant. In this paper, we develop a complete framework applicable to 3D pathology analytical imaging, with an application to whole slide images of sequential liver slices for 3D vessel structure analysis. The analysis workflow consists of image registration, segmentation, vessel cross-section association, interpolation, and volumetric rendering. To identify biologically-meaningful correspondence across adjacent slides, we formulate a similarity function for four association cases. The optimal solution is then obtained by constrained Integer Programming. We quantitatively and qualitatively compare our vessel reconstruction results with human annotations. Validation results indicate a satisfactory concordance as measured both by region-based and distance-based metrics. These results demonstrate a promising 3D vessel analysis framework for whole slide images of liver tissue sections. PMID:27034719

Abstract Background and Purpose Existing imaging modalities of urologic pathology are limited by three-dimensional (3D) representation on a two-dimensional screen. We present 3D-holoscopic imaging as a novel method of representing Digital Imaging and Communications in Medicine data images taken from CT and MRI to produce 3D-holographic representations of anatomy without special eyewear in natural light. 3D-holoscopic technology produces images that are true optical models. This technology is based on physical principles with duplication of light fields. The 3D content is captured in real time with the content viewed by multiple viewers independently of their position, without 3D eyewear. Methods We display 3D-holoscopic anatomy relevant to minimally invasive urologic surgery without the need for 3D eyewear. Results The results have demonstrated that medical 3D-holoscopic content can be displayed on commercially available multiview auto-stereoscopic display. Conclusion The next step is validation studies comparing 3D-Holoscopic imaging with conventional imaging. PMID:23216303

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second (fps) were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction. PMID:24710978

Nonlinear optical imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or second-harmonic generation (SHG) show great potential for in-vivo investigations of tissue. While the microspectroscopic imaging tools are established, automized data evaluation, i.e. image pattern recognition and automized image classification, of nonlinear optical images still bares great possibilities for future developments towards an objective clinical diagnosis. This contribution details the capability of nonlinear microscopy for both 3D visualization of human tissues and automated discrimination between healthy and diseased patterns using ex-vivo human skin samples. By means of CARS image alignment we show how to obtain a quasi-3D model of a skin biopsy, which allows us to trace the tissue structure in different projections. Furthermore, the potential of automated pattern and organization recognition to distinguish between healthy and keloidal skin tissue is discussed. A first classification algorithm employs the intrinsic geometrical features of collagen, which can be efficiently visualized by SHG microscopy. The shape of the collagen pattern allows conclusions about the physiological state of the skin, as the typical wavy collagen structure of healthy skin is disturbed e.g. in keloid formation. Based on the different collagen patterns a quantitative score characterizing the collagen waviness - and hence reflecting the physiological state of the tissue - is obtained. Further, two additional scoring methods for collagen organization, respectively based on a statistical analysis of the mutual organization of fibers and on FFT, are presented.

In this paper, a new stereoscopic 3Dimaging communication system for real-time teleconferencing application is implemented by using IEEE 1394 digital cameras, Intel Xeon server computer system and Microsoft"s DirectShow programming library and its performance is analyzed in terms of image-grabbing frame rate. In the proposed system, two-view images are captured by using two digital cameras and processed in the Intel Xeon server computer system. And then, disparity data is extracted from them and transmitted to the client system with the left image through an information network and in the recipient two-view images are reconstructed and displayed on the stereoscopic 3D display system. The program for controlling the overall system is developed using the Microsoft DirectShow SDK. From some experimental results, it is found that the proposed system can display stereoscopic images in real-time with a full-color of 16 bits and a frame rate of 15fps.

For the first time, the microstructure of directionally solidified ternary eutectics is visualized in three dimensions, using a high-resolution technique of X-ray tomography at the ESRF. The microstructure characterization is conducted with a photon energy, allowing to clearly discriminate the three phases Ag2Al, Al2Cu, and α-Aluminum solid solution. The reconstructed images illustrate the three-dimensional arrangement of the phases. The Ag2Al lamellae perform splitting and merging as well as nucleation and disappearing events during directional solidification.

It the last decades, a formalism of transverse momentum dependent parton distribution functions (TMDs) and of generalised parton distributions (GPDs) has been developed in the context of non-perturbative QCD, opening the way for a tomographic imaging of the nucleon structure. TMDs and GPDs provide complementary three-dimensional descriptions of the nucleon structure in terms of parton densities. They thus contribute, with different approaches, to the understanding of the full phase-space distribution of partons. A selection of HERMES results sensitive to TMDs is presented.

Current training for regional nerve block procedures by anesthesiology residents requires expert supervision and the use of cadavers; both of which are relatively expensive commodities in today's cost-conscious medical environment. We are developing methods to augment and eventually replace these training procedures with real-time and realistic computer visualizations and manipulations of the anatomical structures involved in anesthesiology procedures, such as nerve plexus injections (e.g., celiac blocks). The initial work is focused on visualizations: both static images and rotational renderings. From the initial results, a coherent paradigm for virtual patient and scene representation will be developed.

It the last decades, a formalism of transverse momentum dependent parton distribution functions (TMDs) and of generalised parton distributions (GPDs) has been developed in the context of non-perturbative QCD, opening the way for a tomographic imaging of the nucleon structure. TMDs and GPDs provide complementary three-dimensional descriptions of the nucleon structure in terms of parton densities. They thus contribute, with different approaches, to the understanding of the full phase-space distribution of partons. A selection of HERMES results sensitive to TMDs is presented.

Pulmonary CT images can provide detailed information about the regional structure and function of the respiratory system. Prior to any of these analyses, however, the lungs must be identified in the CT data sets. A popular animal model for understanding lung physiology and pathophysiology is the sheep. In this paper we describe a lung segmentation algorithm for CT images of sheep. The algorithm has two main steps. The first step is lung extraction, which identifies the lung region using a technique based on optimal thresholding and connected components analysis. The second step is lung separation, which separates the left lung from the right lung by identifying the central fissure using an anatomy-based method incorporating dynamic programming and a line filter algorithm. The lung segmentation algorithm has been validated by comparing our automatic method to manual analysis for five pulmonary CT datasets. The RMS error between the computer-defined and manually-traced boundary is 0.96 mm. The segmentation requires approximately 10 minutes for a 512x512x400 dataset on a PC workstation (2.40 GHZ CPU, 2.0 GB RAM), while it takes human observer approximately two hours to accomplish the same task.

In this paper, the authors present a weighted geometrical features (WGF) registration algorithm. Its efficacy is demonstrated by combining points and a surface. The technique is an extension of Besl and McKay`s iterative closest point (ICP) algorithm. The authors use the WGF algorithm to register X-ray computed tomography (CT) and T2-weighted magnetic resonance (MR) volume head images acquired from eleven patients that underwent craniotomies in a neurosurgical clinical trial. Each patient had five external markers attached to transcutaneous posts screwed into the outer table of the skull. The authors define registration error as the distance between positions of corresponding markers that are not used for registration. The CT and MR images are registered using fiducial points (marker positions) only, a surface only, and various weighted combinations of points and a surface. The CT surface is derived from contours corresponding to the inner surface of the skull. The MR surface is derived from contours corresponding to the cerebrospinal fluid (CSF)-dura interface. Registration using points and a surface is found to be significantly more accurate than registration using only points or a surface.

Arterial spin labeling (ASL) is a non-invasive technique that can quantitatively measure cerebral blood flow (CBF). While traditionally ASL employs 2D EPI or spiral acquisition trajectories, single-shot 3D GRASE is gaining popularity in ASL due to inherent SNR advantage and spatial coverage. However, a major limitation of 3D GRASE is through-plane blurring caused by T2 decay. A novel technique combining 3D GRASE and a PROPELLER trajectory (3DGP) is presented to minimize through-plane blurring without sacrificing perfusion sensitivity or increasing total scan time. Full brain perfusion images were acquired at a 3×3×5mm3 nominal voxel size with Q2TIPS-FAIR as the ASL preparation sequence. Data from 5 healthy subjects was acquired on a GE 1.5T scanner in less than 4 minutes per subject. While showing good agreement in CBF quantification with 3D GRASE, 3DGP demonstrated reduced through-plane blurring, improved anatomical details, high repeatability and robustness against motion, making it suitable for routine clinical use. PMID:21254211

Non-uniqueness of satellite gravity interpretation has traditionally been reduced by using a priori information from seismic tomography models. This reduction in the non-uniqueness has been based on velocity-density conversion formulas or user interpretation of the 3D subsurface structures (objects) based on the seismic tomography models and then forward modelling these objects. However, this form of object-based approach has been done without a standardized methodology on how to extract the subsurface structures from the 3D models. In this research, a 3D object-oriented image analysis (3D OOA) approach was implemented to extract the 3D subsurface structures from geophysical data. The approach was applied on a 3D shear wave seismic tomography model of the central part of the East African Rift System. Subsequently, the extracted 3D objects from the tomography model were reconstructed in the 3D interactive modelling environment IGMAS+, and their density contrast values were calculated using an object-based inversion technique to calculate the forward signal of the objects and compare it with the measured satellite gravity. Thus, a new object-based approach was implemented to interpret and extract the 3D subsurface objects from 3D geophysical data. We also introduce a new approach to constrain the interpretation of the satellite gravity measurements that can be applied using any 3D geophysical model.

A three-dimensional (3D) structure designed by our proposed algorithm can simultaneously exhibit multiple two-dimensional patterns. The 3D structure provides multiple patterns having directional characteristics by distributing the effects of the artefacts. In this study, we proposed an iterative algorithm to improve the image quality of the exhibited patterns and have verified the effectiveness of the proposed algorithm using numerical simulations. Moreover, we fabricated different 3D glass structures (an octagonal prism, a cube and a sphere) using the proposed algorithm. All 3D structures exhibit four patterns, and different patterns can be observed depending on the viewing direction. PMID:27137021

After taking off her shoes and jacket, she places them in a bin. She then takes her laptop out of its case and places it in a separate bin. As the items move through the x-ray machine, the woman waits for a sign from security personnel to pass through the metal detector. Today, she was lucky; she did not encounter any delays. The man behind her, however, was asked to step inside a large circular tube, raise his hands above his head, and have his whole body scanned. If you have ever witnessed a full-body scan at the airport, you may have witnessed terahertz imaging. Terahertz wavelengths are located between microwave and infrared on the electromagnetic spectrum. When exposed to these wavelengths, certain materials such as clothing, thin metal, sheet rock, and insulation become transparent. At airports, terahertz radiation can illuminate guns, knives, or explosives hidden underneath a passenger s clothing. At NASA s Kennedy Space Center, terahertz wavelengths have assisted in the inspection of materials like insulating foam on the external tanks of the now-retired space shuttle. "The foam we used on the external tank was a little denser than Styrofoam, but not much," says Robert Youngquist, a physicist at Kennedy. The problem, he explains, was that "we lost a space shuttle by having a chunk of foam fall off from the external fuel tank and hit the orbiter." To uncover any potential defects in the foam covering, such as voids or air pockets, that could keep the material from staying in place, NASA employed terahertz imaging to see through the foam. For many years, the technique ensured the integrity of the material on the external tanks.

3Dimaging has a significant impact on many challenges in life sciences, because biology is a 3-dimensional phenomenon. Current 3Dimaging-technologies (various types MRI, PET, SPECT) are labeled, i.e. they trace the localization of a specific compound in the body. In contrast, 3D MALDI mass spectrometry-imaging (MALDI-MSI) is a label-free method imaging the spatial distribution of molecular compounds. It complements 3Dimaging labeled methods, immunohistochemistry, and genetics-based methods. However, 3D MALDI-MSI cannot tap its full potential due to the lack of statistical methods for analysis and interpretation of large and complex 3D datasets. To overcome this, we established a complete and robust 3D MALDI-MSI pipeline combined with efficient computational data analysis methods for 3D edge preserving image denoising, 3D spatial segmentation as well as finding colocalized m/z values, which will be reviewed here in detail. Furthermore, we explain, why the integration and correlation of the MALDI imaging data with other imaging modalities allows to enhance the interpretation of the molecular data and provides visualization of molecular patterns that may otherwise not be apparent. Therefore, a 3D data acquisition workflow is described generating a set of 3 different dimensional images representing the same anatomies. First, an in-vitro MRI measurement is performed which results in a three-dimensional image modality representing the 3D structure of the measured object. After sectioning the 3D object into N consecutive slices, all N slices are scanned using an optical digital scanner, enabling for performing the MS measurements. Scanning the individual sections results into low-resolution images, which define the base coordinate system for the whole pipeline. The scanned images conclude the information from the spatial (MRI) and the mass spectrometric (MALDI-MSI) dimension and are used for the spatial three-dimensional reconstruction of the object performed by image

Many real time ultrasound (US) guided therapies can benefit from management of motion-induced anatomical changes with respect to a previously acquired computerized anatomy model. Spatial calibration is a prerequisite to transforming US image information to the reference frame of the anatomy model. We present a new method for calibrating 3D US volumes using intramodality image registration, derived from the ‘hand-eye’ calibration technique. The method is fully automated by implementing data rejection based on sensor displacements, automatic registration over overlapping image regions, and a self-consistency error metric evaluated continuously during calibration. We also present a novel method for validating US calibrations based on measurement of physical phantom displacements within US images. Both calibration and validation can be performed on arbitrary phantoms. Results indicate that normalized mutual information and localized cross correlation produce the most accurate 3D US registrations for calibration. Volumetric image alignment is more accurate and reproducible than point selection for validating the calibrations, yielding <1.5 mm root mean square error, a significant improvement relative to previously reported hand-eye US calibration results. Comparison of two different phantoms for calibration and for validation revealed significant differences for validation (p = 0.003) but not for calibration (p = 0.795).

Geological structures in outcrops or hand specimens are inherently three dimensional (3D), and therefore better understandable if viewed in 3D. While 3D models can easily be created, manipulated, and looked at from all sides on the computer screen (e.g., using photogrammetry or laser scanning data), 3D visualizations for publications or conference posters are much more challenging as they have to live in a 2D-world (i.e., on a sheet of paper). Perspective 2D visualizations of 3D models do not fully transmit the "feeling and depth of the third dimension" to the audience; but this feeling is desirable for a better examination and understanding in 3D of the structure under consideration. One of the very few possibilities to generate real 3Dimages, which work on a 2D display, is by using so-called stereoscopic images. Stereoscopic images are two images of the same object recorded from two slightly offset viewpoints. Special glasses and techniques have to be used to make sure that one image is seen only by one eye, and the other image is seen by the other eye, which together lead to the "3D effect". Geoscientists are often familiar with such 3Dimages. For example, geomorphologists traditionally view stereographic orthophotos by employing a mirror-steroscope. Nowadays, petroleum-geoscientists examine high-resolution 3D seismic data sets in special 3D visualization rooms. One of the methods for generating and viewing a stereoscopic image, which does not require a high-tech viewing device, is to create a so-called anaglyph. The principle is to overlay two images saturated in red and cyan, respectively. The two images are then viewed through red-cyan-stereoscopic glasses. This method is simple and cost-effective, but has some drawbacks in preserving colors accurately. A similar method is used in 3D movies, where polarized light or shuttering techniques are used to separate the left from the right image, which allows preserving the original colors. The advantage of red

This picture is a three-dimensional perspective view of Death Valley, California. This view was constructed by overlaying a SIR-C radar image on a U.S. Geological Survey digital elevation map. The SIR-C image is centered at 36.629 degrees north latitude and 117.069 degrees west longitude. We are looking at Stove Pipe Wells, which is the bright rectangle located in the center of the picture frame. Our vantage point is located atop a large alluvial fan centered at the mouth of Cottonwood Canyon. In the foreground on the left, we can see the sand dunes near Stove Pipe Wells. In the background on the left, the Valley floor gradually falls in elevation toward Badwater, the lowest spot in the United States. In the background on the right we can see Tucki Mountain. This SIR-C/X-SAR supersite is an area of extensive field investigations and has been visited by both Space Radar Lab astronaut crews. Elevations in the Valley range from 70 meters (230 feet) below sea level, the lowest in the United States, to more than 3,300 meters (10,800 feet) above sea level. Scientists are using SIR-C/X-SAR data from Death Valley to help the answer a number of different questions about Earth's geology. One question concerns how alluvial fans are formed and change through time under the influence of climatic changes and earthquakes. Alluvial fans are gravel deposits that wash down from the mountains over time. They are visible in the image as circular, fan-shaped bright areas extending into the darker valley floor from the mountains. Information about the alluvial fans helps scientists study Earth's ancient climate. Scientists know the fans are built up through climatic and tectonic processes and they will use the SIR-C/X-SAR data to understand the nature and rates of weathering processes on the fans, soil formation and the transport of sand and dust by the wind. SIR-C/X-SAR's sensitivity to centimeter-scale (inch-scale) roughness provides detailed maps of surface texture. Such information

This picture is a three-dimensional perspective view of Death Valley, California. This view was constructed by overlaying a SIR-C radar image on a U.S. Geological Survey digital elevation map. The SIR-C image is centered at 36.629 degrees north latitude and 117.069 degrees west longitude. We are looking at Stove Pipe Wells, which is the bright rectangle located in the center of the picture frame. Our vantage point is located atop a large alluvial fan centered at the mouth of Cottonwood Canyon. In the foreground on the left, we can see the sand dunes near Stove Pipe Wells. In the background on the left, the Valley floor gradually falls in elevation toward Badwater, the lowest spot in the United States. In the background on the right we can see Tucki Mountain. This SIR-C/X-SAR supersite is an area of extensive field investigations and has been visited by both Space Radar Lab astronaut crews. Elevations in the Valley range from 70 meters (230 feet) below sea level, the lowest in the United States, to more than 3,300 meters (10,800 feet) above sea level. Scientists are using SIR-C/X-SAR data from Death Valley to help the answer a number of different questions about Earth's geology. One question concerns how alluvial fans are formed and change through time under the influence of climatic changes and earthquakes. Alluvial fans are gravel deposits that wash down from the mountains over time. They are visible in the image as circular, fan-shaped bright areas extending into the darker valley floor from the mountains. Information about the alluvial fans helps scientists study Earth's ancient climate. Scientists know the fans are built up through climatic and tectonic processes and they will use the SIR-C/X-SAR data to understand the nature and rates of weathering processes on the fans, soil formation and the transport of sand and dust by the wind. SIR-C/X-SAR's sensitivity to centimeter-scale (inch-scale) roughness provides detailed maps of surface texture. Such information

Although computer processing power and network bandwidth are rapidly increasing, the average desktop is still not able to rapidly process large datasets such as 3-D medical image volumes. We have therefore developed a server side approach to this problem, in which a high performance graphics server accepts commands from web clients to load, process and render 3-Dimage volumes and models. The renderings are saved as 2-D snapshots on the server, where they are uploaded and displayed on the client. User interactions with the graphic interface on the client side are translated into additional commands to manipulate the 3-D scene, after which the server re-renders the scene and sends a new image to the client. Example forms-based and Java-based clients are described for a brain mapping application, but the techniques should be applicable to multiple domains where 3-D medical image visualization is of interest. PMID:11825248

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a rapidly developing technique for the characterization of a wide range of materials. Recently, advances in instrumentation and sample preparation approaches have provided the ability to perform 3D molecular imaging experiments. Polyatomic ion beams, such as C60, and gas cluster ion beams, often Arn (n = 500-4000), substantially reduce the subsurface damage accumulation associated with continued bombardment of organic samples with atomic beams. In this review, the capabilities of the technique are discussed and examples of the 3Dimaging approach for the analysis of model membrane systems, plant single cell, and tissue samples are presented. Ongoing challenges for 3D ToF-SIMS imaging are also discussed along with recent developments that might offer improved 3Dimaging prospects in the near future. PMID:25708631

3D ultrasound (US) provides physicians with a better understanding of human anatomy. By manipulating the 3D US data set, physicians can observe the anatomy in 3D from a number of different view directions and obtain 2D US images that would not be possible to directly acquire with the US probe. In order for 3D US to be in widespread clinical use, creation and manipulation of the 3D US data should be done at interactive times. This is a challenging task due to the large amount of data to be processed. Our group previously reported interactive 3D US imaging using a programmable mediaprocessor, Texas Instruments TMS320C80, which has been in clinical use. In this work, we present the algorithms we have developed for real-time 3D US using a newer and more powerful mediaprocessor, called MAP-CA. MAP-CA is a very long instruction word (VLIW) processor developed for multimedia applications. It has multiple execution units, a 32-kbyte data cache and a programmable DMA controller called the data streamer (DS). A forward mapping 6 DOF (for a freehand 3D US system based on magnetic position sensor for tracking the US probe) reconstruction algorithm with zero- order interpolation is achieved in 11.8 msec (84.7 frame/sec) per 512x512 8-bit US image. For 3D visualization of the reconstructed 3D US data sets, we used volume rendering and in particular the shear-warp factorization with the maximum intensity projection (MIP) rendering. 3D visualization is achieved in 53.6 msec (18.6 frames/sec) for a 128x128x128 8-bit volume and in 410.3 msec (2.4 frames/sec) for a 256x256x256 8-bit volume.

3D surface-enhanced Raman scattering (SERS) imaging with highly symmetric 3D silver microparticles as a SERS substrate was developed. Although the synthesis method is purely chemical and does not involve lithography, the synthesized nanoporous silver microparticles possess a regular hexapod shape and octahedral symmetry. By using p-aminothiophenol (PATP) as a probe molecule, the 3D enhancement patterns of the particles were shown to be very regular and predictable, resembling the particle shape and exhibiting symmetry. An application to the detection of 3D inhomogeneity in a polymer blend, which relies on the predictable enhancement pattern of the substrate, is presented. 3D SERS imaging using the substrate also provides an improvement in spatial resolution along the Z axis, which is a challenge for Raman measurement in polymers, especially layered polymeric systems. PMID:27240138

3D organotypic culture models such as organoids and multicellular tumor spheroids (MCTS) are becoming more widely used for drug discovery and toxicology screening. As a result, 3D culture technologies adapted for high-throughput screening formats are prevalent. While a multitude of assays have been reported and validated for high-throughput imaging (HTI) and high-content screening (HCS) for novel drug discovery and toxicology, limited HTI/HCS with large compound libraries have been reported. Nonetheless, 3D HTI instrumentation technology is advancing and this technology is now on the verge of allowing for 3D HCS of thousands of samples. This review focuses on the state-of-the-art high-throughput imaging systems, including hardware and software, and recent literature examples of 3D organotypic culture models employing this technology for drug discovery and toxicology screening. PMID:26608110

Non-uniqueness of satellite gravity interpretation has been usually reduced by using a priori information from various sources, e.g. seismic tomography models. The reduction in non-uniqueness has been based on velocity-density conversion formulas or user interpretation for 3D subsurface structures (objects) in seismic tomography models. However, these processes introduce additional uncertainty through the conversion relations due to the dependency on the other physical parameters such as temperature and pressure, or through the bias in the interpretation due to user choices and experience. In this research, a new methodology is introduced to extract the 3D subsurface structures from 3D geophysical data using a state-of-art 3D Object Oriented Image Analysis (OOA) technique. 3D OOA is tested using a set of synthetic models that simulate the real situation in the study area of this research. Then, 3D OOA is used to extract 3D subsurface objects from a real 3D seismic tomography model. The extracted 3D objects are used to reconstruct a forward model and its response is compared with the measured satellite gravity. Finally, the result of the forward modelling, based on the extracted 3D objects, is used to constrain the inversion process of satellite gravity data. Through this work, a new object-based approach is introduced to interpret and extract the 3D subsurface objects from 3D geophysical data. This can be used to constrain modelling and inversion of potential field data using the extracted 3D subsurface structures from other methods. In summary, a new approach is introduced to constrain inversion of satellite gravity measurements and enhance interpretation capabilities.

Bonded materials are used in many critical applications, making it important to determine the state of the adhesive during service or aging. It is also of importance, in many cases, to determine if the adhesive has uniformly and completely covered the area to be joined. Through dual transducer scanning, focused and unfocused transducers, and immersion scanning, the uniformity and adherence of a visco-elastic material can be evaluated. In this report, ultrasonic scanning parameters will be optimized experimentally with guidance from simulation tools including Wave 2000 pro and Imagine 3D. We explored optimizing the contrast ratio by varying the interrogation frequency and also by adjusting the distance between the transducer and bond line. An improvement in contrast should also increase the ability to detect differences in compositions and viscosity of the bonded layer. By maximizing the contrast the quality of the visco-elastic bond can be determined, and imperfections detected before adhesive failure.

A novel encryption algorithm to cipher digital images is presented in this work. The digital image is rendering into a three-dimensional (3D) lattice and the protocol consists of two phases: the confusion phase where 24 chaotic Cat maps are applied and the diffusion phase where a 3D cellular automata is evolved. The encryption method is shown to be secure against the most important cryptanalytic attacks.

Integral imaging is a three dimensional (3D) display technology without any additional equipment. A new system is proposed in this paper which consists of the elemental images of real images in real mode (RIRM) and the ones of virtual images in real mode (VIRM). The real images in real mode are the same as the conventional integral images. The virtual images in real mode are obtained by changing the coordinates of the corresponding points in elemental images which can be reconstructed by the lens array in virtual space. In order to reduce the spot size of the reconstructed images, the diffuser in conventional integral imaging is given up in the proposed method. Then the spot size is nearly 1/20 of that in the conventional system. And an optical integral imaging system is constructed to confirm that our proposed method opens a new way for the application of the passive 3D display technology.

A low-gravity environment, in space or ground-based facilities such as drop towers, provides a unique setting for study of combustion mechanisms. Understanding the physical phenomena controlling the ignition and spread of flames in microgravity has importance for space safety as well as better characterization of dynamical and chemical combustion processes which are normally masked by buoyancy and other gravity-related effects. Even the use of so-called 'limiting cases' or the construction of 1-D or 2-D models and experiments fail to make the analysis of combustion simultaneously simple and accurate. Ideally, to bridge the gap between chemistry and fluid mechanics in microgravity combustion, species concentrations and temperature profiles are needed throughout the flame. However, restrictions associated with performing measurements in reduced gravity, especially size and weight considerations, have generally limited microgravity combustion studies to the capture of flame emissions on film or video laser Schlieren imaging and (intrusive) temperature measurements using thermocouples. Given the development of detailed theoretical models, more sophisticated studies are needed to provide the kind of quantitative data necessary to characterize the properties of microgravity combustion processes as well as provide accurate feedback to improve the predictive capabilities of the computational models. While there have been a myriad of fluid mechanical visualization studies in microgravity combustion, little experimental work has been completed to obtain reactant and product concentrations within a microgravity flame. This is largely due to the fact that traditional sampling methods (quenching microprobes using GC and/or mass spec analysis) are too heavy, slow, and cumbersome for microgravity experiments. Non-intrusive optical spectroscopic techniques have - up until now - also required excessively bulky, power hungry equipment. However, with the advent of near-IR diode

Purpose Susceptibility-Weighted Imaging (SWI) in neuroimaging can be challenging due to long scan times of 3D Gradient Recalled Echo (GRE), while faster techniques such as 3D interleaved EPI (iEPI) are prone to motion artifacts. Here we outline and implement a 3D Short-Axis Propeller Echo-Planar Imaging (SAP-EPI) trajectory as a faster, motion-correctable approach for SWI. Methods Experiments were conducted on a 3T MRI system. 3D SAP-EPI, 3D iEPI, and 3D GRE SWI scans were acquired on two volunteers. Controlled motion experiments were conducted to test the motion-correction capability of 3D SAP-EPI. 3D SAP-EPI SWI data were acquired on two pediatric patients as a potential alternative to 2D GRE used clinically. Results 3D GRE images had a better target resolution (0.47 × 0.94 × 2mm, scan time = 5min), iEPI and SAP-EPI images (resolution = 0.94 × 0.94 × 2mm) were acquired in a faster scan time (1:52min) with twice the brain coverage. SAP-EPI showed motion-correction capability and some immunity to undersampling from rejected data. Conclusion While 3D SAP-EPI suffers from some geometric distortion, its short scan time and motion-correction capability suggest that SAP-EPI may be a useful alternative to GRE and iEPI for use in SWI, particularly in uncooperative patients. PMID:24956237

To film the moving fish in the glass tank, light will be bent at the interface of air and glass, glass and water. Based on binocular stereo vision and refraction principle, we establish a mathematical model of 3Dimage correlation to reconstruct the 3D coordinates of samples in the water. Marking speckle in fish surface, a series of real-time speckle images of swimming fish will be obtained by two high-speed cameras, and instantaneous 3D shape, strain, displacement etc. of fish will be reconstructed.

The Imaging Technologies group at De Montfort University has developed an integral 3Dimaging system, which is seen as the most likely vehicle for 3D television avoiding psychological effects. To create real fascinating three-dimensional television programs, a virtual studio that performs the task of generating, editing and integrating the 3D contents involving virtual and real scenes is required. The paper presents, for the first time, the procedures, factors and methods of integrating computer-generated virtual scenes with real objects captured using the 3D integral imaging camera system. The method of computer generation of 3D integral images, where the lens array is modelled instead of the physical camera is described. In the model each micro-lens that captures different elemental images of the virtual scene is treated as an extended pinhole camera. An integration process named integrated rendering is illustrated. Detailed discussion and deep investigation are focused on depth extraction from captured integral 3Dimages. The depth calculation method from the disparity and the multiple baseline method that is used to improve the precision of depth estimation are also presented. The concept of colour SSD and its further improvement in the precision is proposed and verified.

Reconstruction of 3Dimages from a series of 2D images has been restricted by the limited capacity to decrease the opacity of surrounding tissue. Commercial software that allows color-keying and manipulation of 2D images in true 3D space allowed us to produce 3D reconstructions from pixel based imag...

Range-gated laser imaging technology was proposed in 1966 by LF Gillespiethe in U.S. Army Night Vision Laboratory(NVL). Using pulse laser and intensified charge-coupled device(ICCD) as light source and detector respectively, range-gated laser imaging technology can realize space-slice imaging while restraining the atmospheric backs-catter, and in turn detect the target effectively, by controlling the delay between the laser pulse and strobe. Owing to the constraints of the development of key components such as narrow pulse laser and gated imaging devices, the research has been progressed slowly in the next few decades. Until the beginning of this century, as the hardware technology continues to mature, this technology has developed rapidly in fields such as night vision, underwater imaging, biomedical imaging, three-dimensional imaging, especially range-gated three-dimensional(3-D) laser imaging field purposing of access to target spatial information. 3-D reconstruction is the processing of restoration of 3-D objects visible surface geometric structure from three-dimensional(2-D) image. Range-gated laser imaging technology can achieve gated imaging of slice space to form a slice image, and in turn provide the distance information corresponding to the slice image. But to inverse the information of 3-D space, we need to obtain the imaging visual field of system, that is, the focal length of the system. Then based on the distance information of the space slice, the spatial information of each unit space corresponding to each pixel can be inversed. Camera calibration is an indispensable step in 3-D reconstruction, including analysis of the internal structure of camera parameters and the external parameters . In order to meet the technical requirements of the range-gated 3-Dimaging, this paper intends to study the calibration of the zoom lens system. After summarizing the camera calibration technique comprehensively, a classic calibration method based on line is

A series of panoramic images are usually used to generate a 720° panorama image. Although panoramic images are typically used for establishing tour guiding systems, in this research, we demonstrate the potential of using panoramic images acquired from multiple sites to create not only 720° panorama, but also three-dimensional (3D) point clouds and 3D indoor models. Since 3D modeling is one of the goals of this research, the location of the panoramic sites needed to be carefully planned in order to maintain a robust result for close-range photogrammetry. After the images are acquired, panoramic images are processed into 720° panoramas, and these panoramas which can be used directly as panorama guiding systems or other applications. In addition to these straightforward applications, interior orientation parameters can also be estimated while generating 720° panorama. These parameters are focal length, principle point, and lens radial distortion. The panoramic images can then be processed with closerange photogrammetry procedures to extract the exterior orientation parameters and generate 3D point clouds. In this research, VisaulSFM, a structure from motion software is used to estimate the exterior orientation, and CMVS toolkit is used to generate 3D point clouds. Next, the 3D point clouds are used as references to create building interior models. In this research, Trimble Sketchup was used to build the model, and the 3D point cloud was added to the determining of locations of building objects using plane finding procedure. In the texturing process, the panorama images are used as the data source for creating model textures. This 3D indoor model was used as an Augmented Reality model replacing a guide map or a floor plan commonly used in an on-line touring guide system. The 3D indoor model generating procedure has been utilized in two research projects: a cultural heritage site at Kinmen, and Taipei Main Station pedestrian zone guidance and navigation system. The

In the fields of industrial design, artistic design and heritage conservation, physical objects are usually digitalized by reverse engineering through some 3D scanning methods. Structured light and photogrammetry are two main methods to acquire 3D information, and both are expensive. Even if these expensive instruments are used, photorealistic 3D models are seldom available. In this paper, a new method to reconstruction photorealistic 3D models using a single camera is proposed. A square plate glued with coded marks is used to place the objects, and a sequence of about 20 images is taken. From the coded marks, the images are calibrated, and a snake algorithm is used to segment object from the background. A rough 3d model is obtained using shape from silhouettes algorithm. The silhouettes are decomposed into a combination of convex curves, which are used to partition the rough 3d model into some convex mesh patches. For each patch, the multi-view photo consistency constraints and smooth regulations are expressed as a finite element formulation, which can be resolved locally, and the information can be exchanged along the patches boundaries. The rough model is deformed into a fine 3d model through such a domain decomposition finite element method. The textures are assigned to each element mesh, and a photorealistic 3D model is got finally. A toy pig is used to verify the algorithm, and the result is exciting.

Reconstruction of the three-dimensional (3D) surface of an object to be examined is widely used for structure analysis in science and many biological questions require information about their true 3D structure. For Scanning Electron Microscopy (SEM) there has been no efficient non-destructive solution for reconstruction of the surface morphology to date. The well-known method of recording stereo pair images generates a 3D stereoscope reconstruction of a section, but not of the complete sample surface. We present a simple and non-destructive method of 3D surface reconstruction from SEM samples based on the principles of optical close range photogrammetry. In optical close range photogrammetry a series of overlapping photos is used to generate a 3D model of the surface of an object. We adapted this method to the special SEM requirements. Instead of moving a detector around the object, the object itself was rotated. A series of overlapping photos was stitched and converted into a 3D model using the software commonly used for optical photogrammetry. A rabbit kidney glomerulus was used to demonstrate the workflow of this adaption. The reconstruction produced a realistic and high-resolution 3D mesh model of the glomerular surface. The study showed that SEM micrographs are suitable for 3D reconstruction by optical photogrammetry. This new approach is a simple and useful method of 3D surface reconstruction and suitable for various applications in research and teaching. PMID:26073969

AIM: To compare 3D Black Blood turbo spin echo (TSE) sampling perfection with application-optimized contrast using different flip angle evolution (SPACE) vs 2D TSE in evaluating atherosclerotic plaques in multiple vascular territories. METHODS: The carotid, aortic, and femoral arterial walls of 16 patients at risk for cardiovascular or atherosclerotic disease were studied using both 3D black blood magnetic resonance imaging SPACE and conventional 2D multi-contrast TSE sequences using a consolidated imaging approach in the same imaging session. Qualitative and quantitative analyses were performed on the images. Agreement of morphometric measurements between the two imaging sequences was assessed using a two-sample t-test, calculation of the intra-class correlation coefficient and by the method of linear regression and Bland-Altman analyses. RESULTS: No statistically significant qualitative differences were found between the 3D SPACE and 2D TSE techniques for images of the carotids and aorta. For images of the femoral arteries, however, there were statistically significant differences in all four qualitative scores between the two techniques. Using the current approach, 3D SPACE is suboptimal for femoral imaging. However, this may be due to coils not being optimized for femoral imaging. Quantitatively, in our study, higher mean total vessel area measurements for the 3D SPACE technique across all three vascular beds were observed. No significant differences in lumen area for both the right and left carotids were observed between the two techniques. Overall, a significant-correlation existed between measures obtained between the two approaches. CONCLUSION: Qualitative and quantitative measurements between 3D SPACE and 2D TSE techniques are comparable. 3D-SPACE may be a feasible approach in the evaluation of cardiovascular patients. PMID:24876923

In orthognathic surgery, the framing of 3D-surgical planning that considers the balance between the front and back positions and the symmetry of the jawbone, as well as the dental occlusion of teeth, is essential. In this study, a support system for orthodontic surgery to visualize the changes in the mandible and the occlusal condition and to determine the optimum position in mandibular osteotomy has been developed. By integrating the operating portion of a tooth model that is to determine the optimum occlusal position by manipulating the entity tooth model and the 3D-CT skeletal images (3Dimage display portion) that are simultaneously displayed in real-time, the determination of the mandibular position and posture in which the improvement of skeletal morphology and occlusal condition is considered, is possible. The realistic operation of the entity model and the virtual 3Dimage display enabled the construction of a surgical simulation system that involves augmented reality.

A novel 3-D filtering method is presented for speckle reduction and detail preservation in automated 3-D ultrasound images. First, texture features of an image are analyzed by using the improved quadtree (QT) decomposition. Then, the optimal homogeneous and the obvious heterogeneous regions are selected from QT decomposition results. Finally, diffusion parameters and diffusion process are automatically decided based on the properties of these two selected regions. The computing time needed for 2-D speckle reduction is very short. However, the computing time required for 3-D speckle reduction is often hundreds of times longer than 2-D speckle reduction. This may limit its potential application in practice. Because this new filter can adaptively adjust the time step of iteration, the computation time is reduced effectively. Both synthetic and real 3-D ultrasound images are used to evaluate the proposed filter. It is shown that this filter is superior to other methods in both practicality and efficiency. PMID:26366596

Indoor localization is an important research topic for both of the robot and signal processing communities. In recent years, image-based localization is also employed in indoor environment for the easy availability of the necessary equipment. After capturing an image and sending it to an image database, the best matching image is returned with the navigation information. By allowing further camera pose estimation, the image-based localization system with the use of Structure-from-Motion reconstruction model can achieve higher accuracy than the methods of searching through a 2D image database. However, this emerging technique is still only on the use of outdoor environment. In this paper, we introduce the 3D SfM model based image-based localization system into the indoor localization task. We capture images of the indoor environment and reconstruct the 3D model. On the localization task, we simply use the images captured by a mobile to match the 3D reconstructed model to localize the image. In this process, we use the visual words and the approximate nearest neighbor methods to accelerate the process of nding the query feature's correspondences. Within the visual words, we conduct linear search in detecting the correspondences. From the experiments, we nd that the image-based localization method based on 3D SfM model gives good localization result based on both accuracy and speed.

Robust and fully automatic 3D registration of serial-section microscopic images is critical for detailed anatomical reconstruction of large biological specimens, such as reconstructions of dense neuronal tissues or 3D histology reconstruction to gain new structural insights. However, robust and fully automatic 3Dimage registration for biological data is difficult due to complex deformations, unbalanced staining and variations on data appearance. This study presents a fully automatic and robust 3D registration technique for microscopic image reconstruction, and we demonstrate our method on two ssTEM datasets of drosophila brain neural tissues, serial confocal laser scanning microscopic images of a drosophila brain, serial histopathological images of renal cortical tissues and a synthetic test case. The results show that the presented fully automatic method is promising to reassemble continuous volumes and minimize artificial deformations for all data and outperforms four state-of-the-art 3D registration techniques to consistently produce solid 3D reconstructed anatomies with less discontinuities and deformations. PMID:26449756

The evaluation of vertebral deformations is of great importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is oriented towards the computed tomography (CT) and magnetic resonance (MR) imaging techniques, as they can provide a detailed 3D representation of vertebrae, the established methods for the evaluation of vertebral deformations still provide only a two-dimensional (2D) geometrical description. Segmentation of vertebrae in 3D may therefore not only improve their visualization, but also provide reliable and accurate 3D measurements of vertebral deformations. In this paper we propose a method for 3D segmentation of individual vertebral bodies that can be performed in CT and MR images. Initialized with a single point inside the vertebral body, the segmentation is performed by optimizing the parameters of a 3D deterministic model of the vertebral body to achieve the best match of the model to the vertebral body in the image. The performance of the proposed method was evaluated on five CT (40 vertebrae) and five T2-weighted MR (40 vertebrae) spine images, among them five are normal and five are pathological. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images and that the proposed model can describe a variety of vertebral body shapes. The method may be therefore used for initializing whole vertebra segmentation or reliably describing vertebral body deformations.

Robust and fully automatic 3D registration of serial-section microscopic images is critical for detailed anatomical reconstruction of large biological specimens, such as reconstructions of dense neuronal tissues or 3D histology reconstruction to gain new structural insights. However, robust and fully automatic 3Dimage registration for biological data is difficult due to complex deformations, unbalanced staining and variations on data appearance. This study presents a fully automatic and robust 3D registration technique for microscopic image reconstruction, and we demonstrate our method on two ssTEM datasets of drosophila brain neural tissues, serial confocal laser scanning microscopic images of a drosophila brain, serial histopathological images of renal cortical tissues and a synthetic test case. The results show that the presented fully automatic method is promising to reassemble continuous volumes and minimize artificial deformations for all data and outperforms four state-of-the-art 3D registration techniques to consistently produce solid 3D reconstructed anatomies with less discontinuities and deformations. PMID:26449756

In recent years, it is required to develop a system for 3D capture of archives in museums and galleries. In visualizing of 3D object, it is important to reproduce both color and glossiness accurately. Our final goal is to construct digital archival systems in museum and internet or virtual museum via World Wide Web. To achieve our goal, we have developed gonio-photometric imaging system by using high accurate multi-spectral camera and 3D digitizer. In this paper, gonio-photometric imaging method is introduced for recording 3D object. 5-bands images of the object are taken under 7 different illuminants angles. The 5-band image sequences are then analyzed on the basis of both dichromatic reflection model and Phong model to extract gonio-photometric property of the object. The images of the 3D object under illuminants with arbitrary spectral radiant distribution, illuminating angles, and visual points are rendered by using OpenGL with the 3D shape and gonio-photometric property.

Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

Magnetic susceptibility is the physical property for T2*-weighted magnetic resonance imaging (T2*MRI). The invention relates to methods for reconstructing an internal distribution (3D map) of magnetic susceptibility values, .chi. (x,y,z), of an object, from 3D T2*MRI phase images, by using Computed Inverse Magnetic Resonance Imaging (CIMRI) tomography. The CIMRI technique solves the inverse problem of the 3D convolution by executing a 3D Total Variation (TV) regularized iterative convolution scheme, using a split Bregman iteration algorithm. The reconstruction of .chi. (x,y,z) can be designed for low-pass, band-pass, and high-pass features by using a convolution kernel that is modified from the standard dipole kernel. Multiple reconstructions can be implemented in parallel, and averaging the reconstructions can suppress noise. 4D dynamic magnetic susceptibility tomography can be implemented by reconstructing a 3D susceptibility volume from a 3D phase volume by performing 3D CIMRI magnetic susceptibility tomography at each snapshot time.

Within the field of tissue engineering there is an emphasis on studying 3-D live tissue structures. Consequently, to investigate and identify cellular activities and phenotypes in a 3-D environment for all in vitro experiments, including shape, migration/proliferation and axon projection, it is necessary to adopt an optical imaging system that enables monitoring 3-D cellular activities and morphology through the thickness of the construct for an extended culture period without cell labeling. This paper describes a new 3-D tracking algorithm developed for Cell-IQ®, an automated cell imaging platform, which has been equipped with an environmental chamber optimized to enable capturing time-lapse sequences of live cell images over a long-term period without cell labeling. As an integral part of the algorithm, a novel auto-focusing procedure was developed for phase contrast microscopy equipped with 20x and 40x objectives, to provide a more accurate estimation of cell growth/trajectories by allowing 3-D voxels to be computed at high spatiotemporal resolution and cell density. A pilot study was carried out in a phantom system consisting of horizontally aligned nanofiber layers (with precise spacing between them), to mimic features well exemplified in cellular activities of neuronal growth in a 3-D environment. This was followed by detailed investigations concerning axonal projections and dendritic circuitry formation in a 3-D tissue engineering construct. Preliminary work on primary animal neuronal cells in response to chemoattractant and topographic cue within the scaffolds has produced encouraging results.

During spinal neurosurgery, patient-specific information, planning, and annotation such as vertebral labels can be mapped from preoperative 3D CT to intraoperative 2D radiographs via image-based 3D-2D registration. Such registration has been shown to provide a potentially valuable means of decision support in target localization as well as quality assurance of the surgical product. However, robust registration can be challenged by mismatch in image content between the preoperative CT and intraoperative radiographs, arising, for example, from anatomical deformation or the presence of surgical tools within the radiograph. In this work, we develop and evaluate methods for automatically mitigating the effect of content mismatch by leveraging the surgical planning data to assign greater weight to anatomical regions known to be reliable for registration and vital to the surgical task while removing problematic regions that are highly deformable or often occluded by surgical tools. We investigated two approaches to assigning variable weight (i.e., "masking") to image content and/or the similarity metric: (1) masking the preoperative 3D CT ("volumetric masking"); and (2) masking within the 2D similarity metric calculation ("projection masking"). The accuracy of registration was evaluated in terms of projection distance error (PDE) in 61 cases selected from an IRB-approved clinical study. The best performing of the masking techniques was found to reduce the rate of gross failure (PDE > 20 mm) from 11.48% to 5.57% in this challenging retrospective data set. These approaches provided robustness to content mismatch and eliminated distinct failure modes of registration. Such improvement was gained without additional workflow and has motivated incorporation of the masking methods within a system under development for prospective clinical studies.

Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer. PMID:26547117

3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we develop and perform initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and use these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparing to ground truth digital and physical phantom images. The performance of 4DCBCT- and 4DCT- based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms, and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery. PMID:25905722

3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we developed and performed initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and used these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparison to ground truth digital and physical phantom images. The performance of 4DCBCT-based and 4DCT-based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery.

A ~1 MHz piezoelectric micromachined ultrasonic transducer (pMUT) array with ultra-high element density and low crosstalk is proposed for the first time. This novel pMUT array is based on a nano-layer spin-coating lead zirconium titanium film technique and can be fabricated with high element density using a relatively simple process. Accordingly, key fabrication processes such as thick piezoelectric film deposition, low-stress Si-SOI bonding and bulk silicon removal have been successfully developed. The novel fine-pitch 6 × 6 pMUT arrays can all work at the desired frequency (~1 MHz) with good uniformity, high performance and potential IC integration compatibility. The minimum interspace is ~20 μm, the smallest that has ever been achieved to the best of our knowledge. These arrays can be potentially used to steer ultrasound beams and implement high quality 3-D medical imaging applications. PMID:23896705

Based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D)city modeling, a method of fast 3D building modeling using the images from UAV carrying four-combined camera is studied. Firstly, by contrasting and analyzing the mosaic structures of the existing four-combined cameras, a new type of four-combined camera with special design of overlap images is designed, which improves the self-calibration function to achieve the high precision imaging by automatically eliminating the error of machinery deformation and the time lag with every exposure, and further reduce the weight of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of building surfaces and the texture extraction. Finally, two tests that are aerial photography with large scale mapping of 1:1000 and 3D building construction in Shandong University of Science and Technology and aerial photography with large scale mapping of 1:500 and 3D building construction in Henan University of Urban Construction, provide authentication model for construction of 3D building based on combined wide-angle camera images from UAV system. It is demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D building production, and the technology solution in this paper offers a new, fast and technical plan for the 3D expression of the city landscape, fine modeling and visualization.

One of the main issues in the application of multiple-point statistics (MPS) to the simulation of three-dimensional (3D) blocks is the lack of a suitable 3D training image. In this work, we compare three methods of overcoming this issue using information coming from bidimensional (2D) training images. One approach is based on the aggregation of probabilities. The other approaches are novel. One relies on merging the lists obtained using the impala algorithm from diverse 2D training images, creating a list of compatible data events that is then used for the MPS simulation. The other (s2Dcd) is based on sequential simulations of 2D slices constrained by the conditioning data computed at the previous simulation steps. These three methods are tested on the reproduction of two 3Dimages that are used as references, and on a real case study where two training images of sedimentary structures are considered. The tests show that it is possible to obtain 3D MPS simulations with at least two 2D training images. The simulations obtained, in particular those obtained with the s2Dcd method, are close to the references, according to a number of comparison criteria. The CPU time required to simulate with the method s2Dcd is from two to four orders of magnitude smaller than the one required by a MPS simulation performed using a 3D training image, while the results obtained are comparable. This computational efficiency and the possibility of using MPS for 3D simulation without the need for a 3D training image facilitates the inclusion of MPS in Monte Carlo, uncertainty evaluation, and stochastic inverse problems frameworks.

Systematic transrectal ultrasound (TRUS)-guided biopsy is the standard method for a definitive diagnosis of prostate cancer. However, this biopsy approach uses two-dimensional (2D) ultrasound images to guide biopsy and can miss up to 30% of prostate cancers. We are developing a molecular image-directed, three-dimensional (3D) ultrasound imageguided biopsy system for improved detection of prostate cancer. The system consists of a 3D mechanical localization system and software workstation for image segmentation, registration, and biopsy planning. In order to plan biopsy in a 3D prostate, we developed an automatic segmentation method based wavelet transform. In order to incorporate PET/CT images into ultrasound-guided biopsy, we developed image registration methods to fuse TRUS and PET/CT images. The segmentation method was tested in ten patients with a DICE overlap ratio of 92.4% +/- 1.1 %. The registration method has been tested in phantoms. The biopsy system was tested in prostate phantoms and 3D ultrasound images were acquired from two human patients. We are integrating the system for PET/CT directed, 3D ultrasound-guided, targeted biopsy in human patients.

A fundamental step in the generation of visually detailed 3D city models is the acquisition of high fidelity 3D data. Typical approaches employ DSM representations usually derived from Lidar (Light Detection and Ranging) airborne scanning or image based procedures. In this contribution, we focus on the fusion of data from both these methods in order to enhance or complete them. Particularly, we combine an existing Lidar and orthomosaic dataset (used as reference), with a new aerial image acquisition (including both vertical and oblique imagery) of higher resolution, which was carried out in the area of Kallithea, in Athens, Greece. In a preliminary step, a digital orthophoto and a DSM is generated from the aerial images in an arbitrary reference system, by employing a Structure from Motion and dense stereo matching framework. The image-to-Lidar registration is performed by 2D feature (SIFT and SURF) extraction and matching among the two orthophotos. The established point correspondences are assigned with 3D coordinates through interpolation on the reference Lidar surface, are then backprojected onto the aerial images, and finally matched with 2D image features located in the vicinity of the backprojected 3D points. Consequently, these points serve as Ground Control Points with appropriate weights for final orientation and calibration of the images through a bundle adjustment solution. By these means, the aerial imagery which is optimally aligned to the reference dataset can be used for the generation of an enhanced and more accurately textured 3D city model.

In recent years, it is required to develop a system for 3D capture of archives in museums and galleries. In visualizing of 3D object, it is important to reproduce both color and glossiness accurately. Our final goal is to construct digital archival systems in museum and Internet or virtual museum via World Wide Web. To archive our goal, we have developed the multi-spectral imaging systems to record and estimate reflectance spectra of the art paints based on principal component analysis and Wiener estimation method. In this paper, Gonio photometric imaging method is introduced for recording of 3D object. Five-band images of the object are taken under seven different illuminants angles. The set of five-band images are then analyzed on the basis of both dichromatic reflection model and Phong model to extract Gonio photometric information of the object. Prediction of reproduced images of the object under several illuminants and illumination angles is demonstrated and images that are synthesized with 3D wire frame image taken by 3D digitizer are also presented.

The Space Dynamics Laboratory (SDL), working with Naval Research Laboratory (NRL) and industry leaders Advanced Scientific Concepts (ASC) and Hood Technology Corporation, has developed a small SWAP (size, weight, and power) 3Dimaging flash ladar (LAser Detection And Ranging) sensor system concept design for small tactical unmanned air systems (STUAS). The design utilizes an ASC 3D flash ladar camera and laser in a Hood Technology gyro-stabilized gimbal system. The design is an autonomous, intelligent, geo-aware sensor system that supplies real-time 3D terrain and target images. Flash ladar and visible camera data are processed at the sensor using a custom digitizer/frame grabber with compression. Mounted in the aft housing are power, controls, processing computers, and GPS/INS. The onboard processor controls pointing and handles image data, detection algorithms and queuing. The small SWAP 3Dimaging flash ladar sensor system generates georeferenced terrain and target images with a low probability of false return and <10 cm range accuracy through foliage in real-time. The 3Dimaging flash ladar is designed for a STUAS with a complete system SWAP estimate of <9 kg, <0.2 m3 and <350 W power. The system is modeled using LadarSIM, a MATLAB® and Simulink®- based ladar system simulator designed and developed by the Center for Advanced Imaging Ladar (CAIL) at Utah State University. We will present the concept design and modeled performance predictions.

In this study, we developed a three-dimensional (3D) computed tomography (CT) in vivo imaging system for imaging small insects with micrometer resolution. The 3D CT imaging system, referred to as 3D PIXE-micron-CT (PIXEμCT), uses characteristic X-rays produced by ion microbeam bombardment of a metal target. PIXEμCT was used to observe the body organs and internal structure of a living Drosophila melanogaster. Although the organs of the thorax were clearly imaged, the digestive organs in the abdominal cavity could not be clearly discerned initially, with the exception of the rectum and the Malpighian tubule. To enhance the abdominal images, a barium sulfate powder radiocontrast agent was added. For the first time, 3Dimages of the ventriculus of a living D. melanogaster were obtained. Our results showed that PIXEμCT can provide in vivo 3D-CT images that reflect correctly the structure of individual living organs, which is expected to be very useful in biological research.

Summary Deconvolution techniques have been widely used for restoring the 3-D quantitative information of an unknown specimen observed using a wide-field fluorescence microscope. Deconv, an open-source deconvolution software package, was developed for 3-D quantitative fluorescence microscopy imaging and was released under the GNU Public License. Deconv provides numerical routines for simulation of a 3-D point spread function and deconvolution routines implemented three constrained iterative deconvolution algorithms: one based on a Poisson noise model and two others based on a Gaussian noise model. These algorithms are presented and evaluated using synthetic images and experimentally obtained microscope images, and the use of the library is explained. Deconv allows users to assess the utility of these deconvolution algorithms and to determine which are suited for a particular imaging application. The design of Deconv makes it easy for deconvolution capabilities to be incorporated into existing imaging applications. PMID:19941558

We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 +/- 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy.

Threat Image Projection (TIP) plays an important role in aviation security. In order to evaluate human security screeners in determining threats, TIP systems project images of realistic threat items into the images of the passenger baggage being scanned. In this proof of concept paper, we propose a 3D TIP method which can be integrated within new 3D Computed Tomography (CT) screening systems. In order to make the threat items appear as if they were genuinely located in the scanned bag, appropriate CT metal artefacts are generated in the resulting TIP images according to the scan orientation, the passenger bag content and the material of the inserted threat items. This process is performed in the projection domain using a novel methodology based on the Radon Transform. The obtained results using challenging 3D CT baggage images are very promising in terms of plausibility and realism.

Purpose: Imaging phantoms are important tools for researchers and technicians, but they can be costly and difficult to customize. Three dimensional (3D) printing is a widely available rapid prototyping technique that enables the fabrication of objects with 3D computer generated geometries. It is ideal for quickly producing customized, low cost, multimodal, reusable imaging phantoms. This work validates the use of 3D printed phantoms by comparing CT and PET scans of a 3D printed phantom and a commercial “Micro Deluxe” phantom. This report also presents results from a customized 3D printed PET/MRI phantom, and a customized high resolution imaging phantom with sub-mm features. Methods: CT and PET scans of a 3D printed phantom and a commercial Micro Deluxe (Data Spectrum Corporation, USA) phantom with 1.2, 1.6, 2.4, 3.2, 4.0, and 4.8 mm diameter hot rods were acquired. The measured PET and CT rod sizes, activities, and attenuation coefficients were compared. A PET/MRI scan of a custom 3D printed phantom with hot and cold rods was performed, with photon attenuation and normalization measurements performed with a separate 3D printed normalization phantom. X-ray transmission scans of a customized two level high resolution 3D printed phantom with sub-mm features were also performed. Results: Results show very good agreement between commercial and 3D printed micro deluxe phantoms with less than 3% difference in CT measured rod diameter, less than 5% difference in PET measured rod diameter, and a maximum of 6.2% difference in average rod activity from a 10 min, 333 kBq/ml (9 μCi/ml) Siemens Inveon (Siemens Healthcare, Germany) PET scan. In all cases, these differences were within the measurement uncertainties of our setups. PET/MRI scans successfully identified 3D printed hot and cold rods on PET and MRI modalities. X-ray projection images of a 3D printed high resolution phantom identified features as small as 350 μm wide. Conclusions: This work shows that 3D printed

To model the true shape of MRI brain images, automatically classified T1-weighted 3D MRI images (gray matter, white matter, cerebrospinal fluid, scalp/bone and background) are utilized for simulation of grayscale data and imaging artifacts. For each class, Gaussian distribution of grayscale values is assumed, and mean and variance are computed from grayscale images. A random generator fills up the class images with Gauss-distributed grayscale values. Since grayscale values of neighboring voxels are not correlated, a Gaussian low-pass filtering is done, preserving class region borders. To simulate anatomical variability, a Gaussian distribution in space with user-defined mean and variance can be added at any user-defined position. Several imaging artifacts can be added: (1) to simulate partial volume effects, every voxel is averaged with neighboring voxels if they have a different class label; (2) a linear or quadratic bias field can be added with user-defined strength and orientation; (3) additional background noise can be added; and (4) artifacts left over after spoiling can be simulated by adding a band with increasing/decreasing grayscale values. With this method, realistic-looking simulated MRI images can be produced to test classification and segmentation algorithms regarding accuracy and robustness even in the presence of artifacts.

The paper considers specific features of ultrasonic visualization of gas bubbles in a liquid or a medium of like soft biological tissue type under conditions when the size of scatterers is comparable to the acoustic wavelength. It was proposed to use styrofoam specimens as the experimental model of stationary gas bubbles. Patterns of ultrasound scattering by a styrofoam sphere in water were obtained experimentally. It was shown that the measurement results agree well with the prediction of the classical theoretical model of scattering of a plane wave by a perfectly soft sphere. Several experiments were performed illustrating the specific features of visualizing millimeter-sized bubbles. A Terason commercial ultrasonic scanner was used; gelatin specimens with embedded styrofoam spheres served as the objects of study. The simulation and experimental results showed that when bubbles with diameters of <1 mm are visualized, it is impossible to measure the diameter of scatterers because bubbles of different diameters are imaged as bright spots of identical diameter, which is equal to the scanner resolution. To eliminate this difficulty, it is recommended to use the results of theoretical simulation performed in this study, which revealed a monotonic increase in the backscattered signal intensity with an increase in bubble radius. An ultrasonic visualization mode is proposed in which the brightness of scattered signals is used to differentiate between bubbles of different size.

Understanding the relationship between brain function and behavior remains a major challenge in neuroscience. Photoacoustic tomography (PAT) is an emerging technique that allows for noninvasive in vivo brain imaging at micrometer-millisecond spatiotemporal resolution. In this article, a novel, miniaturized 3D wearable PAT (3D-wPAT) technique is described for brain imaging in behaving rats. 3D-wPAT has three layers of fully functional acoustic transducer arrays. Phantom imaging experiments revealed that the in-plane X-Y spatial resolutions were ~200 μm for each acoustic detection layer. The functional imaging capacity of 3D-wPAT was demonstrated by mapping the cerebral oxygen saturation via multi-wavelength irradiation in behaving hyperoxic rats. In addition, we demonstrated that 3D-wPAT could be used for monitoring sensory stimulus-evoked responses in behaving rats by measuring hemodynamic responses in the primary visual cortex during visual stimulation. Together, these results show the potential of 3D-wPAT for brain study in behaving rodents. PMID:27146026

The dynamic visual image modeling for 3D synthetic scenes by using dynamic multichannel binocular visual image based on the mobile self-organizing network. Technologies of 3D modeling synthetic scenes have been widely used in kinds of industries. The main purpose of this paper is to use multiple networks of dynamic visual monitors and sensors to observe an unattended area, to use the advantages of mobile network in rural areas for improving existing mobile network information service further and providing personalized information services. The goal of displaying is to provide perfect representation of synthetic scenes. Using low-power dynamic visual monitors and temperature/humidity sensor or GPS installed in the node equipment, monitoring data will be sent at scheduled time. Then through the mobile self-organizing network, 3D model is rebuilt by synthesizing the returned images. On this basis, we formalize a novel algorithm for multichannel binocular visual 3Dimages based on fast 3D modeling. Taking advantage of these low prices mobile, mobile self-organizing networks can get a large number of video from where is not suitable for human observation or unable to reach, and accurately synthetic 3D scene. This application will play a great role in promoting its application in agriculture.

We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3Dimage pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

In the non-invasive brain imaging with near-infrared light, precise head model is of great significance to the forward model and the image reconstruction. To deal with the individual difference of human head tissues and the problem of the irregular curvature, in this paper, we extracted head structure with Mimics software from the MRI image of a volunteer. This scheme makes it possible to assign the optical parameters to every layer of the head tissues reasonably and solve the diffusion equation with the finite-element analysis. During the solution of the inverse problem, a semi-3D reconstruction algorithm is adopted to trade off the computation cost and accuracy between the full 3-D and the 2-D reconstructions. In this scheme, the changes in the optical properties of the inclusions are assumed either axially invariable or confined to the imaging plane, while the 3-D nature of the photon migration is still retained. This therefore leads to a 2-D inverse issue with the matched 3-D forward model. Simulation results show that comparing to the 3-D reconstruction algorithm, the Semi-3D reconstruction algorithm cut 27% the calculation time consumption.

Understanding the relationship between brain function and behavior remains a major challenge in neuroscience. Photoacoustic tomography (PAT) is an emerging technique that allows for noninvasive in vivo brain imaging at micrometer-millisecond spatiotemporal resolution. In this article, a novel, miniaturized 3D wearable PAT (3D-wPAT) technique is described for brain imaging in behaving rats. 3D-wPAT has three layers of fully functional acoustic transducer arrays. Phantom imaging experiments revealed that the in-plane X-Y spatial resolutions were ~200 μm for each acoustic detection layer. The functional imaging capacity of 3D-wPAT was demonstrated by mapping the cerebral oxygen saturation via multi-wavelength irradiation in behaving hyperoxic rats. In addition, we demonstrated that 3D-wPAT could be used for monitoring sensory stimulus-evoked responses in behaving rats by measuring hemodynamic responses in the primary visual cortex during visual stimulation. Together, these results show the potential of 3D-wPAT for brain study in behaving rodents. PMID:27146026

Interaction with 3D information is one of the fundamental and most familiar tasks in virtually all areas of engineering and science. Several recent technological advances pave the way for developing hand gesture recognition capabilities available to all, which will lead to more intuitive and efficient 3D user interfaces (3DUI). These developments can unlock new levels of expression and productivity in all activities concerned with the creation and manipulation of virtual 3D shapes and, specifically, in engineering design. Building fully automated systems for tracking and interpreting hand gestures requires robust and efficient 3Dimaging techniques as well as potent shape classifiers. We survey and explore current and emerging 3Dimaging technologies, and focus, in particular, on those that can be used to build interfaces between the users' hands and the machine. The purpose of this paper is to categorize and highlight the relevant differences between these existing 3Dimaging approaches in terms of the nature of the information provided, output data format, as well as the specific conditions under which these approaches yield reliable data. Furthermore we explore the impact of each of these approaches on the computational cost and reliability of the required image processing algorithms. Finally we highlight the main challenges and opportunities in developing natural user interfaces based on hand gestures, and conclude with some promising directions for future research. [Figure not available: see fulltext.

We describe an approach for external beam radiotherapy of breast cancer that utilizes the three-dimensional (3D) surface information of the breast. The surface data of the breast are obtained from a 3D optical camera that is rigidly mounted on the ceiling of the treatment vault. This 3D camera utilizes light in the visible range therefore it introduces no ionization radiation to the patient. In addition to the surface topographical information of the treated area, the camera also captures gray-scale information that is overlaid on the 3D surface image. This allows us to visualize the skin markers and automatically determine the isocenter position and the beam angles in the breast tangential fields. The field sizes and shapes of the tangential, supraclavicular, and internal mammary gland fields can all be determined according to the 3D surface image of the target. A least-squares method is first introduced for the tangential-field setup that is useful for compensation of the target shape changes. The entire process of capturing the 3D surface data and subsequent calculation of beam parameters typically requires less than 1 min. Our tests on phantom experiments and patient images have achieved the accuracy of 1 mm in shift and 0.5 deg. in rotation. Importantly, the target shape and position changes in each treatment session can both be corrected through this real-time image-guided system.

We have developed prototypes of flatbed-type autostereoscopic display systems using one-dimensional integral imaging method. The integral imaging system reproduces light beams similar of those produced by a real object. Our display architecture is suitable for flatbed configurations because it has a large margin for viewing distance and angle and has continuous motion parallax. We have applied our technology to 15.4-inch displays. We realized horizontal resolution of 480 with 12 parallaxes due to adoption of mosaic pixel arrangement of the display panel. It allows viewers to see high quality autostereoscopic images. Viewing the display from angle allows the viewer to experience 3-Dimages that stand out several centimeters from the surface of the display. Mixed reality of virtual 3-D objects and real objects are also realized on a flatbed display. In seeking reproduction of natural 3-Dimages on the flatbed display, we developed proprietary software. The fast playback of the CG movie contents and real-time interaction are realized with the aid of a graphics card. Realization of the safety 3-Dimages to the human beings is very important. Therefore, we have measured the effects on the visual function and evaluated the biological effects. For example, the accommodation and convergence were measured at the same time. The various biological effects are also measured before and after the task of watching 3-Dimages. We have found that our displays show better results than those to a conventional stereoscopic display. The new technology opens up new areas of application for 3-D displays, including arcade games, e-learning, simulations of buildings and landscapes, and even 3-D menus in restaurants.

The main objective of this paper is to discuss on the effectiveness of visualising terrain draped with Unmanned Aerial Vehicle (UAV) images generated from different contour intervals using Unity 3D game engine in online environment. The study area that was tested in this project was oil palm plantation at Sintok, Kedah. The contour data used for this study are divided into three different intervals which are 1m, 3m and 5m. ArcGIS software were used to clip the contour data and also UAV images data to be similar size for the overlaying process. The Unity 3D game engine was used as the main platform for developing the system due to its capabilities which can be launch in different platform. The clipped contour data and UAV images data were process and exported into the web format using Unity 3D. Then process continue by publishing it into the web server for comparing the effectiveness of different 3D terrain data (contour data) draped with UAV images. The effectiveness is compared based on the data size, loading time (office and out-of-office hours), response time, visualisation quality, and frame per second (fps). The results were suggest which contour interval is better for developing an effective online 3D terrain visualisation draped with UAV images using Unity 3D game engine. It therefore benefits decision maker and planner related to this field decide on which contour is applicable for their task.

3D process geological models, whether for carbonate or sedimentological systems, have been proposed for modeling realistic subsurface heterogeneity. The problem with such forward process models is that they are not constrained to any subsurface data whether to wells or geophysical surveys. We propose a new method for realistic geological modeling of complex heterogeneity by hybridizing 3D process modeling of geological deposition with conditioning by means of a novel multiple-point geostatistics (MPS) technique termed image quilting (IQ). Image quilting is a pattern-based techniques that stiches together patterns extracted from training images to generate stochastic realizations that look like the training image. In this paper, we illustrate how 3D process model realizations can be used as training images in image quilting. To constrain the realization to seismic data we first interpret each facies in the geophysical data. These interpretation, while overly smooth and not reflecting finer scale variation are used as auxiliary variables in the generation of the image quilting realizations. To condition to well data, we first perform a kriging of the well data to generate a kriging map and kriging variance. The kriging map is used as additional auxiliary variable while the kriging variance is used as a weight given to the kriging derived auxiliary variable. We present an application to a giant offshore reservoir. Starting from seismic advanced attribute analysis and sedimentological interpretation, we build the 3D sedimentological process based model and use it as non-stationary training image for conditional image quilting.

SPECT(single photon emission computed tomography) myocardial imaging is a diagnosis technique that images the region of interest and examines any change induced by disease using a computer after injects intravenously a radiopharmaceutical drug emitting gamma ray and the drug has dispersed evenly in the heart . Myocardial perfusion imaging, which contains functional information, is useful for non-invasive diagnosis of myocardial disease but noises caused by physical factors and low resolution give difficulty in reading the images. In order to help reading myocardial images, this study proposed a method that segments myocardial images and reconstructs the segmented region into a 3Dimage. To resolve difficulty in reading, we segmented the left ventricle, the region of interest, using a level set and modeled the segmented region into a 3Dimage. PMID:20839037

In this paper, we propose a new gold standard data set for the validation of 2D/3Dimage registration algorithms for image guided radiotherapy. A gold standard data set was calculated using a pig head with attached fiducial markers. We used several imaging modalities common in diagnostic imaging or radiotherapy which include 64-slice computed tomography (CT), magnetic resonance imaging (MRI) using T1, T2 and proton density (PD) sequences, and cone beam CT (CBCT) imaging data. Radiographic data were acquired using kilovoltage (kV) and megavoltage (MV) imaging techniques. The image information reflects both anatomy and reliable fiducial marker information, and improves over existing data sets by the level of anatomical detail and image data quality. The markers of three dimensional (3D) and two dimensional (2D) images were segmented using Analyze 9.0 (AnalyzeDirect, Inc) and an in-house software. The projection distance errors (PDE) and the expected target registration errors (TRE) over all the image data sets were found to be less than 1.7 mm and 1.3 mm, respectively. The gold standard data set, obtained with state-of-the-art imaging technology, has the potential to improve the validation of 2D/3D registration algorithms for image guided therapy.

Midsagittal plane (MSP) extraction from 3D brain images is considered as a promising technique for human brain symmetry analysis. In this paper, we present a fast and robust MSP extraction method based on 3D scale-invariant feature transform (SIFT). Unlike the existing brain MSP extraction methods, which mainly rely on the gray similarity, 3D edge registration or parameterized surface matching to determine the fissure plane, our proposed method is based on distinctive 3D SIFT features, in which the fissure plane is determined by parallel 3D SIFT matching and iterative least-median of squares plane regression. By considering the relative scales, orientations and flipped descriptors between two 3D SIFT features, we propose a novel metric to measure the symmetry magnitude for 3D SIFT features. By clustering and indexing the extracted SIFT features using a k-dimensional tree (KD-tree) implemented on graphics processing units, we can match multiple pairs of 3D SIFT features in parallel and solve the optimal MSP on-the-fly. The proposed method is evaluated by synthetic and in vivo datasets, of normal and pathological cases, and validated by comparisons with the state-of-the-art methods. Experimental results demonstrated that our method has achieved a real-time performance with better accuracy yielding an average yaw angle error below 0.91° and an average roll angle error no more than 0.89°.

F3D is written in OpenCL, so it achieve[sic] platform-portable parallelism on modern mutli-core CPUs and many-core GPUs. The interface and mechanims to access F3D core are written in Java as a plugin for Fiji/ImageJ to deliver several key image-processing algorithms necessary to remove artifacts from micro-tomography data. The algorithms consist of data parallel aware filters that can efficiently utilizes[sic] resources and can work on out of core datasets and scale efficiently across multiple accelerators. Optimizing for data parallel filters, streaming out of core datasets, and efficient resource and memory and data managements over complex execution sequence of filters greatly expedites any scientific workflow with image processing requirements. F3D performs several different types of 3Dimage processing operations, such as non-linear filtering using bilateral filtering and/or median filtering and/or morphological operators (MM). F3D gray-level MM operators are one-pass constant time methods that can perform morphological transformations with a line-structuring element oriented in discrete directions. Additionally, MM operators can be applied to gray-scale images, and consist of two parts: (a) a reference shape or structuring element, which is translated over the image, and (b) a mechanism, or operation, that defines the comparisons to be performed between the image and the structuring element. This tool provides a critical component within many complex pipelines such as those for performing automated segmentation of image stacks. F3D is also called a "descendent" of Quant-CT, another software we developed in the past. These two modules are to be integrated in a next version. Further details were reported in: D.M. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high-resolution images of ceramic composites. IEEE International Conference on Big Data, October 2014.

In spite of significant improvements in three-dimensional (3D) display fields, the commercialization of a 3D-only display system is not achieved yet. The mainstream of display market is a high performance two-dimensional (2D) flat panel display (FPD) and the beginning of the high-definition (HD) broadcasting accelerates the opening of the golden age of HD FPDs. Therefore, a 3D display system needs to be able to display a 2D image with high quality. In this paper, two different 3D-2D convertible methods based on integral imaging are compared and categorized for its applications. One method uses a point light source array and a polymer-dispersed liquid crystal and one display panel. The other system adopts two display panels and a lens array. The former system is suitable for mobile applications while the latter is for home applications such as monitors and TVs.

Multi-View Stereo (MVS) as a low cost technique for precise 3D reconstruction can be a rival for laser scanners if the scale of the model is resolved. A fusion of stereo imaging equipment with photogrammetric bundle adjustment and MVS methods, known as photogrammetric MVS, can generate correctly scaled 3D models without using any known object distances. Although a huge number of stereo images (e.g. 200 high resolution images from a small object) captured of the object contains redundant data that allows detailed and accurate 3D reconstruction, the capture and processing time is increased when a vast amount of high resolution images are employed. Moreover, some parts of the object are often missing due to the lack of coverage of all areas. These problems demand a logical selection of the most suitable stereo camera views from the large image dataset. This paper presents a method for clustering and choosing optimal stereo or optionally single images from a large image dataset. The approach focusses on the two key steps of image clustering and iterative image selection. The method is developed within a software application called Imaging Network Designer (IND) and tested by the 3D recording of a gearbox and three metric reference objects. A comparison is made between IND and CMVS, which is a free package for selecting vantage images. The final 3D models obtained from the IND and CMVS approaches are compared with datasets generated with an MMDx Nikon Laser scanner. Results demonstrate that IND can provide a better image selection for MVS than CMVS in terms of surface coordinate uncertainty and completeness.

Industrial robots are commonly used for physically stressful jobs in complex environments. In any case collisions with heavy and high dynamic machines need to be prevented. For this reason the operational range has to be monitored precisely, reliably and meticulously. The advantage of the SwissRanger® SR-3000 is that it delivers intensity images and 3D-information simultaneously of the same scene that conveniently allows 3D-monitoring. Due to that fact automatic real time collision prevention within the robots working space is possible by working with 3D-coordinates.

Biomechanical properties of soft tissues can provide information regarding the local health status. Often the cells in pathological tissues can be found to form a stiff extracellular environment, which is a sensitive, early diagnostic indicator of disease. Quasi-static ultrasonic elasticity imaging provides a way to image the mechanical properties of tissues. Strain images provide a map of the relative tissue stiffness, but ambiguities and artifacts limit its diagnostic value. Accurately mapping intrinsic mechanical parameters of a region may increase diagnostic specificity. However, the inverse problem, whereby force and displacement estimates are used to estimate a constitutive matrix, is ill conditioned. Our method avoids many of the issues involved with solving the inverse problem, such as unknown boundary conditions and incomplete information about the stress field, by building an empirical model directly from measured data. Surface force and volumetric displacement data gathered during imaging are used in conjunction with the AutoProgressive method to teach artificial neural networks the stress-strain relationship of tissues. The Autoprogressive algorithm has been successfully used in many civil engineering applications and to estimate ocular pressure and corneal stiffness; here, we are expanding its use to any tissues imagedultrasonically. We show that force-displacement data recorded with an ultrasound probe and displacements estimated at a few points in the imaged region can be used to estimate the full stress and strain vectors throughout an entire model while only assuming conservation laws. We will also demonstrate methods to parameterize the mechanical properties based on the stress-strain response of trained neural networks. This method is a fundamentally new approach to medical elasticity imaging that for the first time provides full stress and strain vectors from one set of observation data.

A three-dimensional High-resolution Ultrasonic Transmission Tomography (HUTT) system has been developed recently under the sponsorship of the Alfred Mann Institute at the University of Southern California that holds the promise of early detection of breast cancer (mm-size lesions) with greater sensitivity (true positives) and specificity (true negatives) than current x-ray mammograghy. In addition to sub-mm resolution in 3-D, the HUTT system has the unique capability of reliable tissue classification by means of the frequency-dependent attenuation characteristics of individual voxels that are extracted from the tomographic data through novel signal processing methods. These methods yield "multi-band signatures" of the various tissue types that are utilized to achieve reliable tissue differentiation via novel segmentation and classification algorithms. The unparalleled high-resolution and tissue differentiation capabilities of the HUTT system have been demonstrated so far with man-made and animal-tissue phantoms. Illustrative results are presented that corroborate these claims, although several challenges remain to make HUTT a clinically acceptable technology. The next critical step is to collect and analyze data from human subjects (female breasts) in order to demonstrate the key capability of the HUTT system to detect breast lesions early (at the mm-size stage) and to differentiate between malignant and benign lesions in a manner that is far superior (in terms of sensitivity and specificity) to the current x-ray mammography. The key initial application of the HUTT imaging technology is envisioned to be the early (at the mm-size) detection of breast cancer, which represents a major threat to the well-being of women around the world. The potential impact is estimated in hundreds of thousands lives saved, millions of unnecessary biopsies avoided, and billions of dollars saved in national health-care costs every year - to say nothing of the tens of thousands of

Obtaining three-dimensional (3D) information of biologic tissue is important in many medical applications. This paper presents two methods for reconstructing 3D topography of biologic tissue: multiview imaging and structured light illumination. For each method, the working principle is introduced, followed by experimental validation on a diabetic foot model. To compare the performance characteristics of these two imaging methods, a coordinate measuring machine (CMM) is used as a standard control. The wound surface topography of the diabetic foot model is measured by multiview imaging and structured light illumination methods respectively and compared with the CMM measurements. The comparison results show that the structured light illumination method is a promising technique for 3D topographic imaging of biologic tissue.

A method for recovery of a 3D model of a cloud-like structure that is in motion and deforming but approximately governed by magnetic field properties is described. The method allows recovery of the model from a single intensity image in which the structure's silhouette can be observed. The method exploits envelope theory and a magnetic field model. Given one intensity image and the segmented silhouette in the image, the method proceeds without human intervention to produce the 3D model. In addition to allowing 3D model synthesis, the method's capability to yield a very compact description offers further utility. Application of the method to several real-world images is demonstrated.

We describe the application of 2D and 3D data acquisition and mutual registration to the conservation of paintings. RGB color image acquisition, IR and UV fluorescence imaging, together with the more recent hyperspectral imaging (32 bands) are among the most useful techniques in this field. They generally are meant to provide information on the painting materials, on the employed techniques and on the object state of conservation. However, only when the various images are perfectly registered on each other and on the 3D model, no ambiguity is possible and safe conclusions may be drawn. We present the integration of 2D and 3D measurements carried out on two different paintings: "Madonna of the Yarnwinder" by Leonardo da Vinci, and "Portrait of Lionello d'Este", by Pisanello, both painted in the XV century.

We describe the application of 2D and 3D data acquisition and mutual registration to the conservation of paintings. RGB color image acquisition, IR and UV fluorescence imaging, together with the more recent hyperspectral imaging (32 bands) are among the most useful techniques in this field. They generally are meant to provide information on the painting materials, on the employed techniques and on the object state of conservation. However, only when the various images are perfectly registered on each other and on the 3D model, no ambiguity is possible and safe conclusions may be drawn. We present the integration of 2D and 3D measurements carried out on two different paintings: "Madonna of the Yarnwinder" by Leonardo da Vinci, and "Portrait of Lionello d'Este", by Pisanello, both painted in the XV century.

Portable imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often not able to run with sufficient performance on a portable platform. In recent years, advanced multicore DSPs have been introduced that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms like 3D adaptive filtering, improving the image quality of portable medical imaging devices. In this study, the performance of a 3D adaptive filtering algorithm on a digital signal processor (DSP) is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec.

We have applied image analysis methods in the assessment of human kidney perfusion based on 3D dynamic contrast-enhanced (DCE) MRI data. This approach consists of 3D non-rigid image registration of the kidneys and fuzzy C-mean classification of kidney tissues. The proposed registration method reduced motion artifacts in the dynamic images and improved the analysis of kidney compartments (cortex, medulla, and cavities). The dynamic intensity curves show the successive transition of the contrast agent through kidney compartments. The proposed method for motion correction and kidney compartment classification may be used to improve the validity and usefulness of further model-based pharmacokinetic analysis of kidney function.

Photoacoustic imaging is exquisitely sensitive to blood and can infer blood oxygenation based on multispectral images. In this work we present multispectral real-time 3D photoacoustic imaging of blood phantoms. We used a custom-built 128-channel hemispherical transducer array coupled to two Nd:YAG pumped OPO laser systems synchronized to provide double pulse excitation at 680 nm and 1064 nm wavelengths, all during a triggered series of ultrasound pressure measurements lasting less than 300 μs. The results demonstrated that 3D PAI is capable of differentiating between oxygenated and deoxygenated blood at high speed at mm-level resolution.

We here show 3D light sheet microscopy images of fixed and cleared murine colon tissue in-toto, which offer relevant cellular information without the need for physically sectioning the tissue. We have applied the recently developed CUBIC protocol (Susaki et al. Cell 157:726, 2014) for colon tissues and have found that this clearing protocol enables imaging all the way to the central part of the lumen with cellular resolution, thus opening new ways for 3Dimaging of colon samples.

We outline key objectives and capabilities of an Electron-Ion Collider (EIC) — a high-energy and high-luminosity electron-proton/nucleus collider with polarized electron and proton beams. One of goals of a future EIC is to map the 3D (in configuration and momentum spaces) structure of sea quarks and gluons in the nucleon and nuclei. We briefly present and discuss key observables and measurements pertaining to the program of 3Dimaging at an EIC.

Early embryonic heart development is a period of dynamic growth and remodeling, with rapid changes occurring at the tissue, cell, and subcellular levels. A detailed understanding of the events that establish the components of the heart wall has been hampered by a lack of methodologies for three dimensional (3D), high-resolution imaging. Focused ion beam-scanning electron microscopy (FIB-SEM) is a novel technology for imaging3D tissue volumes at the subcellular level. FIB-SEM alternates between imaging the block face with a scanning electron beam and milling away thin sections of tissue with a focused ion beam, allowing for collection and analysis of 3D data. FIB-SEM was used to image the three layers of the day 4 chicken embryo heart: myocardium, cardiac jelly, and endocardium. Individual images obtained with FIB-SEM were comparable in quality and resolution to those obtained with transmission electron microscopy (TEM). Up to 1100 serial images were obtained in 4 nm increments at 4.88 nm resolution, and image stacks were aligned to create volumes 800–1500 μm3 in size. Segmentation of organelles revealed their organization and distinct volume fractions between cardiac wall layers. We conclude that FIB-SEM is a powerful modality for 3D subcellular imaging of the embryonic heart wall. PMID:24742339

A fusion technique which combines two different types of sensory data for 3-D modeling of a navigation space is presented. The sensory data is generated by a vision camera and a laser scanner. The problem of different resolutions for these sensory data was solved by reduced image resolution, fusion of different data, and use of a fuzzy image segmentation technique.

The anaglyph three-dimensional (3D) method is a widely used technique for presenting stereoscopic 3Dimages. Its primary advantages are that it will work on any full-color display and only requires that the user view the anaglyph image using a pair of anaglyph 3D glasses with usually one lens tinted red and the other lens tinted cyan. A common image quality problem of anaglyph 3Dimages is high levels of crosstalk-the incomplete isolation of the left and right image channels such that each eye sees a "ghost" of the opposite perspective view. In printed anaglyph images, the crosstalk levels are often very high-much higher than when anaglyph images are presented on emissive displays. The sources of crosstalk in printed anaglyph images are described and a simulation model is developed that allows the amount of printed anaglyph crosstalk to be estimated based on the spectral characteristics of the light source, paper, ink set, and anaglyph glasses. The model is validated using a visual crosstalk ranking test, which indicates good agreement. The model is then used to consider scenarios for the reduction of crosstalk in printed anaglyph systems and finds a number of options that are likely to reduce crosstalk considerably.

Automatic segmentation and 3D modeling of the knee joint from MR images, is a challenging task. Most of the existing techniques require the tedious manual segmentation of a training set of MRIs. We present an approach that necessitates the manual segmentation of one MR image. It is based on a volumetric active appearance model. First, a dense tetrahedral mesh is automatically created on a reference MR image that is arbitrary selected. Second, a pairwise non-rigid registration between each MRI from a training set and the reference MRI is computed. The non-rigid registration is based on a piece-wise affine deformation using the created tetrahedral mesh. The minimum description length is then used to bring all the MR images into a correspondence. An average image and tetrahedral mesh, as well as a set of main modes of variations, are generated using the established correspondence. Any manual segmentation of the average MRI can be mapped to other MR images using the AAM. The proposed approach has the advantage of simultaneously generating 3D reconstructions of the surface as well as a 3D solid model of the knee joint. The generated surfaces and tetrahedral meshes present the interesting property of fulfilling a correspondence between different MR images. This paper shows preliminary results of the proposed approach. It demonstrates the automatic segmentation and 3D reconstruction of a knee joint obtained by mapping a manual segmentation of a reference image.

By applying a bank of 2D Gabor filters to a blurred image, single-frame blind-image deconvolution (SF BID) is formulated as a 3D tensor factorization (TF) problem, with the key contribution that neither origin nor size of the spatially invariant blurring kernel is required to be known or estimated. Mixing matrix, the original image, and its spatial derivatives are identified from the factors in the Tucker3 model of the multichannel version of the blurred image. Previous approaches to 2D Gabor-filter-bank-based SF BID relied on 2D representation of the multichannel version of the blurred image and matrix factorization methods such as nonnegative matrix factorization (NMF) and independent component analysis (ICA). Unlike matrix factorization-based methods 3D TF preserves local structure in the image. Moreover, 3D TF based on the PARAFAC model is unique up to permutation and scales under very mild conditions. To achieve this, NMF and ICA respectively require enforcement of sparseness and statistical independence constraints on the original image and its spatial derivatives. These constraints are generally not satisfied. The 3D TF-based SF BID method is demonstrated on an experimental defocused red-green-blue image. PMID:19756121

Digital breast tomosynthesis (DBT) is an innovative imaging modality that provides 3D reconstructed images of breast to detect the breast cancer. Projections obtained with an X-ray source moving in a limited angle interval are used to reconstruct 3Dimage of breast. Several reconstruction algorithms are available for DBT imaging. Filtered back projection algorithm has traditionally been used to reconstruct images from projections. Iterative reconstruction algorithms such as algebraic reconstruction technique (ART) were later developed. Recently, compressed sensing based methods have been proposed in tomosynthesis imaging problem. We have developed an object-oriented simulator for 3D digital breast tomosynthesis (DBT) imaging system using C++ programming language. The simulator is capable of implementing different iterative and compressed sensing based reconstruction methods on 3D digital tomosynthesis data sets and phantom models. A user friendly graphical user interface (GUI) helps users to select and run the desired methods on the designed phantom models or real data sets. The simulator has been tested on a phantom study that simulates breast tomosynthesis imaging problem. Results obtained with various methods including algebraic reconstruction technique (ART) and total variation regularized reconstruction techniques (ART+TV) are presented. Reconstruction results of the methods are compared both visually and quantitatively by evaluating performances of the methods using mean structural similarity (MSSIM) values. PMID:24371468

The aim of this article is to build trajectories for virtual endoscopy inside 3D medical images, using the most automatic way. Usually the construction of this trajectory is left to the clinician who must define some points on the path manually using three orthogonal views. But for a complex structure such as the colon, those views give little information on the shape of the object of interest. The path construction in 3Dimages becomes a very tedious task and precise a priori knowledge of the structure is needed to determine a suitable trajectory. We propose a more automatic path tracking method to overcome those drawbacks: we are able to build a path, given only one or two end points and the 3Dimage as inputs. This work is based on previous work by Cohen and Kimmel [Int. J. Comp. Vis. 24 (1) (1997) 57] for extracting paths in 2D images using Fast Marching algorithm. Our original contribution is twofold. On the first hand, we present a general technical contribution which extends minimal paths to 3Dimages and gives new improvements of the approach that are relevant in 2D as well as in 3D to extract linear structures in images. It includes techniques to make the path extraction scheme faster and easier, by reducing the user interaction. We also develop a new method to extract a centered path in tubular structures. Synthetic and real medical images are used to illustrate each contribution. On the other hand, we show that our method can be efficiently applied to the problem of finding a centered path in tubular anatomical structures with minimum interactivity, and that this path can be used for virtual endoscopy. Results are shown in various anatomical regions (colon, brain vessels, arteries) with different 3Dimaging protocols (CT, MR). PMID:11731307

We present a image quality improvement in a parallax barrier (PB)-based multiview autostereoscopic 3D display system under a real-time tracking of positions of a viewer's eyes. The system presented exploits a parallax barrier engineered to offer significantly improved quality of three-dimensional images for a moving viewer without an eyewear under the dynamic eye tracking. The improved image quality includes enhanced uniformity of image brightness, reduced point crosstalk, and no pseudoscopic effects. We control the relative ratio between two parameters i.e., a pixel size and the aperture of a parallax barrier slit to improve uniformity of image brightness at a viewing zone. The eye tracking that monitors positions of a viewer's eyes enables pixel data control software to turn on only pixels for view images near the viewer's eyes (the other pixels turned off), thus reducing point crosstalk. The eye tracking combined software provides right images for the respective eyes, therefore producing no pseudoscopic effects at its zone boundaries. The viewing zone can be spanned over area larger than the central viewing zone offered by a conventional PB-based multiview autostereoscopic 3D display (no eye tracking). Our 3D display system also provides multiviews for motion parallax under eye tracking. More importantly, we demonstrate substantial reduction of point crosstalk of images at the viewing zone, its level being comparable to that of a commercialized eyewear-assisted 3D display system. The multiview autostereoscopic 3D display presented can greatly resolve the point crosstalk problem, which is one of the critical factors that make it difficult for previous technologies for a multiview autostereoscopic 3D display to replace an eyewear-assisted counterpart. PMID:26074575

In this paper a study of 3D ultrasound cardiac segmentation using Active Shape Models (ASM) is presented. The proposed approach is based on a combination of a point distribution model constructed from a multitude of high resolution MRI scans and the appearance model obtained from simulated 3D ultrasound images. Usually the appearance model is learnt from a set of landmarked images. The significant level of noise, the low resolution of 3D ultrasound images (3D US) and the frequent failure to capture the complete wall of the left ventricle (LV) makes automatic or manual landmarking difficult. One possible solution is to use artificially simulated 3D US images since the generated images will match exactly the shape in question. In this way, by varying simulation parameters and generating corresponding images, it is possible to obtain a training set where the image matches the shape exactly. In this work the simulation of ultrasound images is performed by a convolutional approach. The evaluation of segmentation accuracy is performed on both simulated and in vivo images. The results obtained on 567 simulated images had an average error of 1.9 mm (1.73 +/- 0.05 mm for epicardium and 2 +/- 0.07 mm for endocardium, with 95% confidence) with voxel size being 1.1 × 1.1 × 0.7 mm. The error on 20 in vivo data was 3.5 mm (3.44 +/- 0.4 mm for epicardium and 3.73 +/- 0.4 mm for endocardium). In most images the model was able to approximate the borders of myocardium even when the latter was indistinguishable from the surrounding tissues.

In this study we analyze the feasibility of three dimensional (3D) electromagnetic (EM) imaging from a single borehole. The proposed logging tool consists of three mutually orthogonal magnetic dipole sources and multiple three component magnetic field receivers. A sensitivity analysis indicates that the most important sensor configuration for providing 3D geological information about the borehole consists of a transmitter with moment aligned parallel to the axis of the borehole, and receivers aligned perpendicular to the axis. The standard coaxial logging configuration provides the greatest depth of sensitivity compared to other configurations, but offers no information regarding 3D structure. Two other tool configurations in which both the source and receiver are aligned perpendicular to the borehole axis provide some directional information and therefore better image resolution, but not true 3D information. A 3D inversion algorithm has been employed to demonstrate the plausibility of 3D inversion using data collected with the proposed logging tool. This study demonstrates that an increase in image resolution results when three orthogonal sources are incorporated into the logging tool rather than a single axially aligned source.

While three-dimensional tumor models have emerged as valuable tools in cancer research, the ability to longitudinally visualize the 3D tumor architecture restored by these systems is limited with microscopy techniques that provide only qualitative insight into sample depth, or which require terminal fixation for depth-resolved 3Dimaging. Here we report the use of digital holographic microscopy (DHM) as a viable microscopy approach for quantitative, non-destructive longitudinal imaging of in vitro 3D tumor models. Following established methods we prepared 3D cultures of pancreatic cancer cells in overlay geometry on extracellular matrix beds and obtained digital holograms at multiple timepoints throughout the duration of growth. The holograms were digitally processed and the unwrapped phase images were obtained to quantify nodule thickness over time under normal growth, and in cultures subject to chemotherapy treatment. In this manner total nodule volumes are rapidly estimated and demonstrated here to show contrasting time dependent changes during growth and in response to treatment. This work suggests the utility of DHM to quantify changes in 3D structure over time and suggests the further development of this approach for time-lapse monitoring of 3D morphological changes during growth and in response to treatment that would otherwise be impractical to visualize.

Chlorophyll content and distribution in leaf can reflect the plant health and nutrient status of the plant indirectly. It is meaningful to monitor the 3D distribution of chlorophyll in plant science. It can be done by the method in this paper: Firstly, the chlorophyll contents at different point in leaf are measured with the SPAD-502 chlorophyll meter, and the RGN images composed by the channel R, G and NIR are captured with the imaging system. Secondly, the 3D model is built from the RGN images and the RGN texture map containing all the information of R, G and NIR is generated. Thirdly, the regression model between chlorophyll content and color characteristics is established. Finally, the 3D distribution of chlorophyll in rice is captured by mapping the 2D distribution map of chlorophyll calculated by the regression model to the 3D model. This methodology achieves the combination of phenotype and physiology, it can calculated the 3D distribution of chlorophyll in rice well. The color characteristic g is good indicator of chlorophyll content which can be used to measure the 3D distribution of chlorophyll quickly. Moreover, the methodology can be used to high throughout analyze the rice.

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. For this purpose, we previously developed a software platform for high-performance 3D medical image processing, called HPC 3D-MIP platform, which employs increasingly available and affordable commodity computing systems such as the multicore, cluster, and cloud computing systems. To achieve scalable high-performance computing, the platform employed size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D-MIP algorithms, supported task scheduling for efficient load distribution and balancing, and consisted of a layered parallel software libraries that allow image processing applications to share the common functionalities. We evaluated the performance of the HPC 3D-MIP platform by applying it to computationally intensive processes in virtual colonoscopy. Experimental results showed a 12-fold performance improvement on a workstation with 12-core CPUs over the original sequential implementation of the processes, indicating the efficiency of the platform. Analysis of performance scalability based on the Amdahl's law for symmetric multicore chips showed the potential of a high performance scalability of the HPC 3D-MIP platform when a larger number of cores is available. PMID:24910506

One of the key challenges in three-dimensional (3D) medical imaging is to enable the fast turn-around time, which is often required for interactive or real-time response. This inevitably requires not only high computational power but also high memory bandwidth due to the massive amount of data that need to be processed. For this purpose, we previously developed a software platform for high-performance 3D medical image processing, called HPC 3D-MIP platform, which employs increasingly available and affordable commodity computing systems such as the multicore, cluster, and cloud computing systems. To achieve scalable high-performance computing, the platform employed size-adaptive, distributable block volumes as a core data structure for efficient parallelization of a wide range of 3D-MIP algorithms, supported task scheduling for efficient load distribution and balancing, and consisted of a layered parallel software libraries that allow image processing applications to share the common functionalities. We evaluated the performance of the HPC 3D-MIP platform by applying it to computationally intensive processes in virtual colonoscopy. Experimental results showed a 12-fold performance improvement on a workstation with 12-core CPUs over the original sequential implementation of the processes, indicating the efficiency of the platform. Analysis of performance scalability based on the Amdahl’s law for symmetric multicore chips showed the potential of a high performance scalability of the HPC 3D-MIP platform when a larger number of cores is available. PMID:24910506

In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

Background Many three-dimensional (3D) images are routinely collected in biomedical research and a number of digital atlases with associated anatomical and other information have been published. A number of tools are available for viewing this data ranging from commercial visualization packages to freely available, typically system architecture dependent, solutions. Here we discuss an atlas viewer implemented to run on any workstation using the architecture neutral Java programming language. Results We report the development of a freely available Java based viewer for 3Dimage data, descibe the structure and functionality of the viewer and how automated tools can be developed to manage the Java Native Interface code. The viewer allows arbitrary re-sectioning of the data and interactive browsing through the volume. With appropriately formatted data, for example as provided for the Electronic Atlas of the Developing Human Brain, a 3D surface view and anatomical browsing is available. The interface is developed in Java with Java3D providing the 3D rendering. For efficiency the image data is manipulated using the Woolz image-processing library provided as a dynamically linked module for each machine architecture. Conclusion We conclude that Java provides an appropriate environment for efficient development of these tools and techniques exist to allow computationally efficient image-processing libraries to be integrated relatively easily. PMID:15757508

It is very important to observe the vessels of the patient who are dialyzed artificially. An X-ray examination using contrast medium injected to the patient has been used for this purpose up to the present, but sometimes the examination has a risk of radiation damage. Therefore, we developed a safe and easy-to-use system in which 3Dimages of the vessels in the patients are reconstructed very quick from ultrasonic echoes. In this system, a view point for 3D rendering is set on the above position of the ultrasonic transducer, and a ray for the rendering is coincided with an ultrasonic beam. These features enable 3Dimages to be gradually reconstructed in real time while the echoes are being received. A magnetic position sensor system and a special 3D scanner which was developed were adopted for acquiring 3D echo data. In signal processing, intensity inversion technology is carried out before the 3D rendering process in order to detect and emphasize the vessels. With this system, we have acquired echo signals from the vessels in the arm of kidney dialyzed patients and made similar 3Dimages of X-ray angiography with the echoes in a short time such as 4 to 8 seconds.

This paper reflects the contents of the plenary talk given by Nico Felicien Declercq. "UltrasonicImaging of materials" covers a wide technological area with main purpose to look at and to peek inside materials. In an ideal world one would manage to examine materials like a clairvoyant. Fortunately this is impossible hence nature has offered sufficient challenges to mankind to provoke curiosity and to develop science and technology. Here we focus on the appearance of certain undesired physical effects that prohibit direct imaging of materials in ultrasonic C-scans. Furthermore we try to make use of these effects to obtain indirect images of materials and therefore make a virtue of necessity. First we return to one of the oldest quests in the progress of mankind: how thick is ice? Our ancestors must have faced this question early on during migration to Northern Europe and to the America's and Asia. If a physicist or engineer is not provided with helpful tools such as a drill or a device based on ultrasound, it is difficult to determine the ice thickness. Guided waves, similar to those used for nondestructive testing of thin plates in structural health monitoring can be used in combination with the human ear to determine the thickness of ice. To continue with plates, if an image of its interior is desired high frequency ultrasonic pulses can be applied. It is known by the physicist that the resolution depends on the wavelength and that high frequencies usually result in undesirably high damping effects inhibiting deep penetration into the material. To the more practical oriented engineer it is known that it is advantageous to polish surfaces before examination because scattering and diffraction of sound lowers the image resolution. Random scatterers cause some blurriness but cooperating scatters, causing coherent diffraction effects similar to the effects that cause DVD's to show rainbow patterns under sunlight, can cause spooky images and erroneous measurements of

This paper reflects the contents of the plenary talk given by Nico Felicien Declercq. “UltrasonicImaging of materials” covers a wide technological area with main purpose to look at and to peek inside materials. In an ideal world one would manage to examine materials like a clairvoyant. Fortunately this is impossible hence nature has offered sufficient challenges to mankind to provoke curiosity and to develop science and technology. Here we focus on the appearance of certain undesired physical effects that prohibit direct imaging of materials in ultrasonic C-scans. Furthermore we try to make use of these effects to obtain indirect images of materials and therefore make a virtue of necessity. First we return to one of the oldest quests in the progress of mankind: how thick is ice? Our ancestors must have faced this question early on during migration to Northern Europe and to the America’s and Asia. If a physicist or engineer is not provided with helpful tools such as a drill or a device based on ultrasound, it is difficult to determine the ice thickness. Guided waves, similar to those used for nondestructive testing of thin plates in structural health monitoring can be used in combination with the human ear to determine the thickness of ice. To continue with plates, if an image of its interior is desired high frequency ultrasonic pulses can be applied. It is known by the physicist that the resolution depends on the wavelength and that high frequencies usually result in undesirably high damping effects inhibiting deep penetration into the material. To the more practical oriented engineer it is known that it is advantageous to polish surfaces before examination because scattering and diffraction of sound lowers the image resolution. Random scatterers cause some blurriness but cooperating scatters, causing coherent diffraction effects similar to the effects that cause DVD’s to show rainbow patterns under sunlight, can cause spooky images and erroneous

A new algorithm is developed for retrieving the land surface temperature (LST) from the imager radiance observations on board geostationary operational Indian National Satellite (INSAT-3D). The algorithm is developed using the two thermal infrared channels (TIR1 10.3-11.3 µm and TIR2 11.5-12.5 µm) via genetic algorithm (GA). The transfer function that relates LST and thermal radiances is developed using radiative transfer model simulated database. The developed algorithm has been applied on the INSAT-3D observed radiances, and LST retrieved from the developed algorithm has been validated with Moderate Resolution Imaging Spectroradiometer land surface temperature (LST) product. The developed algorithm demonstrates a good accuracy, without significant bias and standard deviations of 1.78 K and 1.41 K during daytime and nighttime, respectively. The newly proposed algorithm performs better than the operational algorithm used for LST retrieval from INSAT-3D satellite. Further, a set of data assimilation experiments is conducted with the Weather Research and Forecasting (WRF) model to assess the impact of INSAT-3D LST on model forecast skill over the Indian region. The assimilation experiments demonstrated a positive impact of the assimilated INSAT-3D LST, particularly on the lower tropospheric temperature and moisture forecasts. The temperature and moisture forecast errors are reduced (as large as 8-10%) with the assimilation of INSAT-3D LST, when compared to forecasts that were obtained without the assimilation of INSAT-3D LST. Results of the additional experiments of comparative performance of two LST products, retrieved from operational and newly proposed algorithms, indicate that the impact of INSAT-3D LST retrieved using newly proposed algorithm is significantly larger compared to the impact of INSAT-3D LST retrieved using operational algorithm.

Accurate and objective evaluation of vertebral deformations is of significant importance in clinical diagnostics and therapy of pathological conditions affecting the spine. Although modern clinical practice is focused on three-dimensional (3D) computed tomography (CT) and magnetic resonance (MR) imaging techniques, the established methods for evaluation of vertebral deformations are limited to measuring deformations in two-dimensional (2D) x-ray images. In this paper, we propose a method for quantitative description of vertebral body deformations by efficient modelling and segmentation of vertebral bodies in 3D. The deformations are evaluated from the parameters of a 3D superquadric model, which is initialized as an elliptical cylinder and then gradually deformed by introducing transformations that yield a more detailed representation of the vertebral body shape. After modelling the vertebral body shape with 25 clinically meaningful parameters and the vertebral body pose with six rigid body parameters, the 3D model is aligned to the observed vertebral body in the 3Dimage. The performance of the method was evaluated on 75 vertebrae from CT and 75 vertebrae from T2-weighted MR spine images, extracted from the thoracolumbar part of normal and pathological spines. The results show that the proposed method can be used for 3D segmentation of vertebral bodies in CT and MR images, as the proposed 3D model is able to describe both normal and pathological vertebral body deformations. The method may therefore be used for initialization of whole vertebra segmentation or for quantitative measurement of vertebral body deformations.

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3Dimage quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within the reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3Dimage reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical

Crack detection for bridge bottom surfaces via remote sensing techniques is undergoing a revolution in the last few years. For such applications, a large amount of images, acquired with high-resolution industrial cameras close to the bottom surfaces with some mobile platform, are required to be stitched into a wide-view single composite image. The conventional idea of stitching a panorama with the affine model or the homographic model always suffers a series of serious problems due to poor texture and out-of-focus blurring introduced by depth of field. In this paper, we present a novel method to seamlessly stitch these images aided by 3D structure lines of bridge bottom surfaces, which are extracted from 3D camera data. First, we propose to initially align each image in geometry based on its rough position and orientation acquired with both a laser range finder (LRF) and a high-precision incremental encoder, and these images are divided into several groups with the rough position and orientation data. Secondly, the 3D structure lines of bridge bottom surfaces are extracted from the 3D cloud points acquired with 3D cameras, which impose additional strong constraints on geometrical alignment of structure lines in adjacent images to perform a position and orientation optimization in each group to increase the local consistency. Thirdly, a homographic refinement between groups is applied to increase the global consistency. Finally, we apply a multi-band blending algorithm to generate a large-view single composite image as seamlessly as possible, which greatly eliminates both the luminance differences and the color deviations between images and further conceals image parallax. Experimental results on a set of representative images acquired from real bridge bottom surfaces illustrate the superiority of our proposed approaches.

Visualizing and analyzing the morphological structure of carotid bifurcations are important for understanding the etiology of carotid atherosclerosis, which is a major cause of stroke and transient ischemic attack. For delineation of vasculatures in the carotid artery, ultrasound examinations have been widely employed because of a noninvasive procedure without ionizing radiation. However, conventional 2D ultrasound imaging has technical limitations in observing the complicated 3D shapes and asymmetric vasodilation of bifurcations. This study aims to propose image-processing techniques for better 3D reconstruction of a carotid bifurcation in a rat by using 2D cross-sectional ultrasound images. A high-resolution ultrasound imaging system with a probe centered at 40MHz was employed to obtain 2D transversal images. The lumen boundaries in each transverse ultrasound image were detected by using three different techniques; an ellipse-fitting, a correlation mapping to visualize the decorrelation of blood flow, and the ellipse-fitting on the correlation map. When the results are compared, the third technique provides relatively good boundary extraction. The incomplete boundaries of arterial lumen caused by acoustic artifacts are somewhat resolved by adopting the correlation mapping and the distortion in the boundary detection near the bifurcation apex was largely reduced by using the ellipse-fitting technique. The 3D lumen geometry of a carotid artery was obtained by volumetric rendering of several 2D slices. For the 3D vasodilatation of the carotid bifurcation, lumen geometries at the contraction and expansion states were simultaneously depicted at various view angles. The present 3D reconstruction methods would be useful for efficient extraction and construction of the 3D lumen geometries of carotid bifurcations from 2D ultrasound images. PMID:24965564

Ionising radiation causes various types of DNA damages including double strand breaks (DSBs). DSBs are often recognized by DNA repair protein ATM which forms gamma-H2AX foci at the site of the DSBs that can be visualized using immunohistochemistry. However most of such experiments are of low throughput in terms of imaging and image analysis techniques. Most of the studies still use manual counting or classification. Hence they are limited to counting a low number of foci per cell (5 foci per nucleus) as the quantification process is extremely labour intensive. Therefore we have developed a high throughput instrumentation and computational pipeline specialized for gamma-H2AX foci quantification. A population of cells with highly clustered foci inside nuclei were imaged, in 3D with submicron resolution, using an in-house developed high throughput image cytometer. Imaging speeds as high as 800 cells/second in 3D were achieved by using HiLo wide-field depth resolved imaging and a remote z-scanning technique. Then the number of foci per cell nucleus were quantified using a 3D extended maxima transform based algorithm. Our results suggests that while most of the other 2D imaging and manual quantification studies can count only up to about 5 foci per nucleus our method is capable of counting more than 100. Moreover we show that 3D analysis is significantly superior compared to the 2D techniques.

In this paper an image-based method founded on mathematical morphology is presented in order to facilitate the segmentation of cerebral structures on 3D magnetic resonance images (MRIs). The segmentation is described as an immersion simulation, applied to the modified gradient image, modeled by a generated 3D region adjacency graph (RAG). The segmentation relies on two main processes: homotopy modification and contour decision. The first one is achieved by a marker extraction stage where homogeneous 3D regions are identified in order to attribute an influence zone only to relevant minima of the image. This stage uses contrasted regions from morphological reconstruction and labeled flat regions constrained by the RAG. The goal of the decision stage is to precisely locate the contours of regions detected by the marker extraction. This decision is performed by a 3D extension of the watershed transform. Upon completion of the segmentation, the outcome of the preceding process is presented to the user for manual selection of the structures of interest (SOI). Results of this approach are described and illustrated with examples of segmented 3D MRIs of the human head.

Cell migration studies in 3D environments become more popular, as cell behaviors in 3D are more similar to the behaviors of cells in a living organism (in vivo). We focus on the 3D angiogenic sprouting in microfluidic devices, where Endothelial Cells (ECs) burrow into the gel matrix and form solid lumen vessels. Phase contrast microscopy is used for long-term observation of the unlabeled ECs in the 3D microfluidic devices. Two template matching based approaches are proposed to automatically detect the unlabeled ECs in the angiogenic sprouts from the acquired experimental phase contrast images. Cell and non-cell templates are obtained from these phase contrast images as the training data. The first approach applies Partial Least Square Regression (PLSR) to find the discriminative features and their corresponding weight to distinguish cells and non-cells, whereas the second approach relies on Principal Component Analysis (PCA) to reduce the template feature dimension and Support Vector Machine (SVM) to find their corresponding weight. Through a sliding window manner, the cells in the test images are detected. We then validate the detection accuracy by comparing the results with the same images acquired with a confocal microscope after cells are fixed and their nuclei are stained. More accurate numerical results are obtained for approach I (PLSR) compared to approach II (PCA & SVM) for cell detection. Automatic cell detection will aid in the understanding of cell migration in 3D environment and in turn result in a better understanding of angiogenesis.

Three dimension medical images have been playing an irreplaceable role in realms of medical treatment, teaching, and research. However, collaborative processing and visualization of 3D medical images on Internet is still one of the biggest challenges to support these activities. Consequently, we present a new application approach for web-based synchronized collaborative processing and visualization of 3D medical Images. Meanwhile, a web-based videoconference function is provided to enhance the performance of the whole system. All the functions of the system can be available with common Web-browsers conveniently, without any extra requirement of client installation. In the end, this paper evaluates the prototype system using 3D medical data sets, which demonstrates the good performance of our system.

The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.